Fixed-term

PhD position for a project titled- “Development of innovative sensor technology for monitoring milk quality, health, and welfare in dairy cattle”

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Project Dairy farming is an important part of global food production, accounting for approximately 10% of the total agricultural market share. Due to genetic advancements and improved feeding and management practices, average milk production per cow per lactation has increased enormously over the past 50 years. However, these modern dairy cows are also more susceptible to production-related disorders. Closely monitoring animal health and welfare is therefore important to continue guaranteeing sustainable milk production. Due to the strong interaction between milk production and the cow’s metabolism, the milk produced contains a great deal of information about udder health and nutritional and metabolic status. For this reason, regular monitoring of the quality and composition of the produced milk is one of the most efficient ways to monitor cow health. Nowadays, online measurements of production levels, conductivity, and milk color are already common in dairy farming. Nevertheless, these milk parameters, in addition to health status, are also influenced by many other factors. For this reason, there is a need for quality parameters that have a more direct link to the cow’s health. The formation of key milk components, such as milk fat, protein, and lactose, is a direct result of feed intake and the cow’s metabolism, as well as the health of the udder tissue. Consequently, regular analysis of these basic components in milk can provide valuable information about the health of individual cows. In this project, an optical prototype sensor will be developed, based on a miniature near-infrared spectrometer, for the online analysis of the basic components in milk. This sensor will be implemented and tested in combination with automatic milking systems. After implementation, the robustness of this sensor will be evaluated and improved using various calibration strategies. Finally, the variation in sensor measurements will be studied in relation to cow health and for the development of monitoring tools to detect abnormal health or negative welfare at an early stage. Profile To conduct this practice-oriented research, the “Livestock Technology” group at KU Leuven is looking for a highly motivated and independent doctoral researcher with: an MSc degree (at least with distinction) in Life Sciences, Industrial Sciences, Engineering Sciences, Bioengineering Sciences or equivalent a creative, critical, analytical, and innovative mindset good communication skills, both in Dutch and English Eager to collaborate in a multidisciplinary team of national and international researchers to discover and develop new techniques strong interest in sensor technology, development, data processing and scientific research the ambition to build a career in sensor development and data processing If you meet these requirements, then you are THE candidate we are looking for, and we would very much like you to apply for this fascinating doctoral position. Experience with scientific data processing software (e.g. Matlab, Python, R, C, Labview or similar) and hands-on engineering, and an interest in dairy farming, are definitely pluses. You are not eligible for this position if you do not hold an MSc degree with at least distinction obtained from a university in the European Economic Community (EEC) within the last 3 years. Offer We offer full-time employment with competitive remuneration for 4 years, preferably starting on September 1, 2026. Our young, dynamic, multidisciplinary, and professional team will provide extensive support in conducting your research and obtaining your doctoral degree. We offer a tailor-made doctoral program within one of the best universities in Europe. Furthermore, we offer the opportunity to collaborate directly with Flemish dairy farmers, the “Hooibeekhoeve” dairy research farm, and milk technology manufacturers. You will also have the opportunity to regularly test your research plan and results with various stakeholders at national and international meetings. This will allow you to build an international network and further develop your communication skills. Interested? More information can be obtained from Prof. Dr. Ben Aernouts, email: ben.aernouts@kuleuven.be. You can apply for this vacancy until 15/07/2026 via our online application system. KU Leuven aims to be an inclusive, respectful, and socially safe community. We embrace diversity among individuals and groups as an asset. Open dialogue and differences in perspective are essential in an ambitious research and teaching environment. In our pursuit of equal opportunities, we acknowledge the consequences of historical inequalities. We do not accept any form of discrimination based on, among other things, sex, gender identity and expression, sexual orientation, age, ethnic or national origin, skin colour, religious belief, neurodivergence, disability, health, or socio-economic status. If you have questions about accessibility or available support, we are happy to assist you at this email address . Application procedure Employment conditions Career opportunities Do you have a question about the online application procedure? Consult our frequently asked questions or send an email to solliciteren@kuleuven.be

Recruitment for Doctoral Researcher (Environmental Chemicals and Endometriosis)

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We are looking for a Doctoral Researcher in the field of molecular toxicology, systems biology, and women’s reproductive health. The position is full-time and will be filled for a fixed-term period of 4 years. The workplace is located at Kauppi Campus, Tampere University.  The Faculty of Medicine and Health Technology (MET) is dedicated to pursuing world-class research and delivering high-quality education in the fields of biomedical engineering, biotechnology, medicine and health technology. We conduct internationally acclaimed basic and applied research.  The position is hosted by the Mechanistic and Applied Toxicology (MAT) research group, a newly established group led by Dr Alexandra Schaffert. MAT develops next-generation, animal testing-free approaches to chemical safety, combining molecular biology, proteomics and computational methods to understand how chemicals affect human health, with a particular focus on endocrine disruption and women’s reproductive health. Job description We are seeking a highly motivated Doctoral Researcher to join EIRIS, a research project investigating how endocrine-disrupting chemicals contribute to endometriosis, a common, painful and historically under-researched condition affecting roughly one in ten women. Despite widespread environmental exposure to endocrine disruptive chemicals, their role in female reproductive disease remains poorly understood. EIRIS is among the first to address this question systematically, building the first comprehensive mechanistic map of how everyday chemical exposures may promote the disease. The project sits at the intersection of environmental health, women’s health and next-generation, animal-free toxicology. Tasks As Doctoral Researcher, you will play a central role in EIRIS, contributing to both the experimental and data-driven parts of the project. Your work will combine structured evidence synthesis, computational/data-oriented analysis, and hands-on wet-lab experiments: Systematically collecting and curating published evidence on chemical effects in endometriosis into a structured, openly available knowledge base using systematic evidence mapping and language model-assisted approaches Establishing human endometrial cell models and carrying out controlled chemical exposure experiments Generating proteomic and secretomic samples (LC-MS/MS) and performing in vitro assays  Biological interpretation of omics, pathway, clustering and network-analysis results Presenting results at conferences, attending trainings, and contributing to publications You will be fully trained in all relevant methods and will undertake short research visits to partner laboratories within Finland and abroad. You will work closely with a computational postdoctoral researcher and an international network of collaborators across toxicology, bioinformatics and women’s health. Prior knowledge in toxicology is welcome but not required, we will provide the toxicological training. What matters most is a solid background in the life sciences, curiosity, careful working habits, willingness to work across both hands-on wet-lab experiments and data-oriented/computational approaches, and a strong interest in a societally important and emerging research question. The selected candidate will be able to focus on their doctoral research full-time and will receive dedicated supervision and mentoring, while being encouraged to develop scientific independence and implement new ideas as part of a supportive, positive and multidisciplinary research environment at the MET faculty. In addition to the doctoral dissertation, the duties of a doctoral researcher include participation in education or other faculty tasks that support your studies.  Requirements: Master’s degree in molecular biology, cell biology, biochemistry, biotechnology, biomedical sciences, toxicology, computational biology, systems biology, bioinformatics, or another closely related life-science field A solid background in life sciences and strong motivation to work at the interface of environmental health, women’s reproductive health and mechanistic toxicology Basic understanding of experimental design, data handling and statistics Interest in learning computational/data-oriented approaches, such as literature curation, omics data interpretation, pathway analysis or network analysis A careful, well-organised and reliable approach to experimental and data work Ability to work both independently and as part of a multidisciplinary team Fluency in English  The following are considered an advantage but are not required: Hands-on laboratory experience, particularly mammalian cell culture and/or molecular biology techniques Experience with literature curation, systematic review/evidence mapping, omics data analysis or basic bioinformatics Familiarity with R, Python or another programming language Experience in toxicology, endocrine disruption, reproductive biology, endometriosis, network biology, ontologies or adverse outcome pathways You need to have completed a relevant Master’s degree before the starting date of employment.  Successful candidates must be pursuing or should be accepted to study towards a doctoral degree in the Doctoral Programme in Medicine, Biosciences and Biomedical Engineering. Please visit the admissions webpage for more information on eligibility requirements. Tampere University is a unique, multidisciplinary, and boldly forward-looking community. Our values are openness, diversity, responsibility, courage, critical thinking, and learner-centeredness. We hope that you can embrace these values and promote them in your work. We offer The starting date is preferably as soon as possible, but latest in November 2026, or as mutually agreed. The position is full-time, and it will be filled for a fixed-term period of 4 years. A trial period of 6 months applies to all our new employees. The salary will be based on both the job requirements and the employee’s personal performance in accordance with the Finnish University Salary System. According to the criteria applied to teaching and research staff, the position of a Doctoral Researcher is placed on level 2-4 of the job requirements scale. A typical starting salary for a Doctoral Researcher is approximately 2770-2900 EUR per month. The salary increases based on experience and the progress of doctoral studies. We are inviting you to be a part of a vibrant, active, and truly multidisciplinary research community. We value interdisciplinarity, as it allows you to expand your research network and exposes you to new perspectives and ideas to solve complex research problems and pursue novel research findings. We are strongly committed to the highest level of scientific research and the provision of high-quality education. At the Faculty of Medicine and Health Technology, you will have access to state-of-the-art research facilities and resources. We offer a collaborative and interdisciplinary research environment, supported by mentoring and structured training opportunities. You will also be enrolled in a doctoral program, providing a comprehensive and supportive framework for completing your PhD. As a member of staff at Tampere University, you will enjoy a range of competitive benefits, such as occupational health care services, flexible work schedule, versatile research infrastructure, modern teaching facilities and a safe and

Postdoctoral Research Fellow in translational neuroimaging

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Position Summary Dr. Jürgen Germann’s Neuroimaging and Brain Modelling Laboratory at the Krembil Research Institute, University Health Network, is seeking a highly motivated Postdoctoral Research Fellow to lead a translational neuroimaging project focused on early diagnosis and disease progression modelling in Parkinson’s disease and related disorders. The successful candidate will play a central role in developing MRI-based, machine learning-driven probability models for differential diagnosis using image-derived features. A key focus will be translating these models into a clinician-facing decision-support tool for real-world implementation. This includes building pipelines that take routine clinical MRI as input and generate patient-specific probabilistic diagnostic outputs to support clinical decision-making. The position offers a unique opportunity to work at the interface of neuroimaging, machine learning, and clinical translation, with a strong focus on high-impact publications and the development of deployable clinical tools. The work will be conducted in a highly multidisciplinary environment, in close collaboration with Dr. Alexandre Boutet (Neuroradiology) and Dr. Anthony Lang (Neurology; Director of the Movement Disorders Program). This opportunity will allow you to: Lead development of machine learning models for imaging-based diagnostic probability estimation Develop and optimize pipelines that generate patient-specific probabilistic predictions from MRI data Design and implement a clinician-facing tool for model deployment and integration into clinical workflows Analyze large-scale multimodal neuroimaging datasets (structural and diffusion MRI) Perform statistical modelling, validation, and calibration of predictive models Contribute to development of clinically interpretable outputs (e.g., probability maps, reports) Work closely with clinical collaborators to ensure usability and relevance of the tool Draft manuscripts, abstracts, and grant applications Present research findings at meetings and conferences  Mentor graduate and undergraduate trainees Collaborate within a highly interdisciplinary team spanning neurology, neuroradiology, medical physics, and data science Duties Lead the development of machine learning models for imaging-based diagnostic probability estimation Develop and optimize pipelines to generate patient-specific probabilistic predictions from MRI data Design and implement a clinician-facing tool to support model deployment and integration into clinical workflows Analyze large-scale multimodal neuroimaging datasets, including structural and diffusion MRI Perform statistical modelling, validation, and calibration of predictive models Contribute to the development of clinically interpretable outputs (e.g., structured reports, atrophy maps) Collaborate closely with clinical partners to ensure usability, interpretability, and clinical relevance of developed tools Qualifications PhD in neuroscience, biomedical engineering, computer science, medical physics, or a related field (obtained within the past 5 years) required Strong programming skills (e.g., Python, R, MATLAB, or similar) Experience with machine learning and statistical modelling Experience with neuroimaging analysis (MRI-based methods preferred) Experience with voxel-based or morphometry-based neuroimaging analyses an asset Experience developing end-to-end pipelines or tools for applied or clinical use an asset Experience with model deployment (e.g., APIs, GUIs, or clinical software pipelines) an asset Familiarity with neuroimaging toolkits (e.g., ANTs, FSL, FreeSurfer, SPM) an asset Ability to work independently and lead projects Strong analytical and problem-solving skills Excellent written and verbal communication skills Demonstrated scientific productivity (e.g., peer-reviewed publications) Interest in translational and clinically impactful research Additional Information Why join UHN?In addition to working alongside some of the most talented and inspiring healthcare professionals in the world, UHN offers a wide range of benefits, programs and perks. It is the comprehensiveness of these offerings that makes it a differentiating factor, allowing you to find value where it matters most to you, now and throughout your career at UHN. Competitive offer packages Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP https://hoopp.com/) Close access to Transit and UHN shuttle service A flexible work environment Opportunities for development and promotions within a large organization Additional perks (multiple corporate discounts including: travel, restaurants, parking, phone plans, auto insurance discounts, on-site gyms, etc.) Current UHN employees must have successfully completed their probationary period, have a good employee record along with satisfactory attendance in accordance with UHN’s attendance management program, to be eligible for consideration. All applications must be submitted before the posting close date. UHN uses email to communicate with selected candidates.  Please ensure you check your email regularly. At University Health Network (UHN), artificial intelligence technologies may be used to assist in the screening, assessment, and selection of candidates for this position. Please be advised that a Criminal Record Check may be required of the successful candidate. Should it be determined that any information provided by a candidate be misleading, inaccurate or incorrect, UHN reserves the right to discontinue with the consideration of their application. UHN is an equal opportunity employer committed to an inclusive recruitment process and workplace. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their requirements known. We thank all applicants for their interest, however, only those selected for further consideration will be contacted. Apply Now

Postdoctoral Researcher in translational cancer research

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Position Summary:We are seeking a postdoctoral researcher with strong expertise in AI/ML to join a major interdisciplinary initiative focused on developing foundation models and secure computational infrastructure for translational cancer research.  The first major objective is to build a general-purpose drug foundation model capable of transfer learning across diverse prediction tasks, including mechanism of action classification, clinical drug response prediction in tumour subtypes, ADMET and toxicity profiling, combinatorial drug synergy, and drug repurposing. The goal is to move beyond task-specific architectures and datasets toward flexible models that can generalize across therapeutic contexts. The second major objective is to develop and apply secure, scalable, and privacy-preserving computational infrastructure to support biomarker discovery across diverse treatment modalities. This will include building agentic AI approaches to harmonize clinical, genomic, and transcriptomic data across public and private cohorts, while assessing the predictive value of DNA and RNA signatures in federated settings where sensitive data remain under local governance. Together, these efforts aim to advance AI-driven drug discovery, biomarker development, and clinical translation by integrating modern machine learning, multimodal biomedical data, and robust distributed analysis frameworks. The successful candidate will work in the Haibe-Kains Lab at the Princess Margaret Cancer Centre, University Health Network. Duties: Design and implement multimodal drug foundation models that integrate molecular graph representations, bulk transcriptomic perturbation signatures, and multi-omics cell-state representations. Develop transfer learning strategies to support diverse drug prediction tasks, including mechanism of action classification, clinical drug response prediction, ADMET and toxicity profiling, combinatorial drug synergy, and drug repurposing. Build flexible AI/ML workflows that reduce reliance on task-specific architectures and enable generalization across therapeutic contexts, tumour subtypes, and treatment modalities. Architect and deploy secure, scalable, and privacy-preserving computational infrastructure for biomarker discovery and translational cancer research. Develop agentic AI-enabled frameworks to support the harmonization, annotation, quality control, and integration of clinical, genomic, and transcriptomic data across public cohorts and private institutional datasets. Implement distributed and federated analysis pipelines in which each contributing dataset can be analysed separately, enabling multi-cohort biomarker assessment without raw data centralization. Develop systematic workflows to evaluate published and user-specified DNA and RNA signatures, including immune, stromal, mutation-based, pathway-level, and treatment-response signatures. Assess the predictive value of molecular signatures across cancer types and treatment modalities, including chemotherapy, targeted therapy, immunotherapy, and emerging therapeutic approaches. Integrate biomarker discovery and immunotherapy inference pipelines with clinical data warehouses to support translational studies in collaboration with clinical, industry, and computational partners. Contribute to responsible data sharing frameworks, data governance processes, IRB/ethics protocols, and regulatory documentation as required. Collaborate closely with computational biologists, software developers, clinicians, and wet-lab scientists to build, validate, and translate predictive models and biomarker discovery workflows. Qualifications Awarded a PhD within the previous 5 years, or an MD or DDS within the previous 10 years in a relevant quantitative or biomedical discipline, including but not limited to: Computational Biology, Bioinformatics, Systems Biology, or Quantitative Genomics; Machine Learning, Artificial Intelligence, Computer Science, or Data Science; Biostatistics, Biomedical Engineering, or related fields Demonstrated experience developing or applying deep learning methods to molecular, biological, clinical, or multi-omics data. Expertise in one or more modern AI/ML approaches relevant to foundation models or representation learning, such as graph neural networks, transformers, generative models, self-supervised learning, few-shot or zero-shot learning, or transfer learning. Strong programming skills in Python and/or R, with practical experience using modern machine learning frameworks and tooling such as PyTorch, Hugging Face, PyTorch Geometric, Deep Graph Library, scikit-learn, or equivalent platforms. Experience working with large-scale biomedical datasets, such as molecular graphs, transcriptomic perturbation profiles, multi-omics data, clinical genomics, electronic health record-derived data, or treatment-response datasets. Proficiency with reproducible workflow management systems such as Snakemake, Nextflow, CWL, or equivalent pipeline frameworks. Familiarity with cloud or high-performance computing environments, such as GCP, AWS, SLURM-based clusters, or equivalent infrastructure. Understanding of data harmonization, privacy-preserving analysis, federated learning, secure distributed computing, or clinical data governance is highly desirable. Strong publication record, commensurate with career stage, in computational biology, AI/ML, bioinformatics, biostatistics, biomedical data science, or related fields. Excellent communication skills and ability to work collaboratively in interdisciplinary teams spanning computational biology, machine learning, software engineering, oncology, and clinical research. Experience with clinical data harmonization (e.g., OMOP CDM, HL7 FHIR) is preferred. Experience designing scalable bioinformatics pipelines for large-scale genomic or transcriptomic datasets, preferred. Understanding of regulatory and data governance requirements in clinical research settings, preferred. Prior collaborative work across computational and clinical or wet-lab research teams, preferred. Additional Information Why join UHN?In addition to working alongside some of the most talented and inspiring healthcare professionals in the world, UHN offers a wide range of benefits, programs and perks. It is the comprehensiveness of these offerings that makes it a differentiating factor, allowing you to find value where it matters most to you, now and throughout your career at UHN. Competitive offer packages Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP https://hoopp.com/) Close access to Transit and UHN shuttle service A flexible work environment Opportunities for development and promotions within a large organization Additional perks (multiple corporate discounts including: travel, restaurants, parking, phone plans, auto insurance discounts, on-site gyms, etc.) Current UHN employees must have successfully completed their probationary period, have a good employee record along with satisfactory attendance in accordance with UHN’s attendance management program, to be eligible for consideration. All applications must be submitted before the posting close date. UHN uses email to communicate with selected candidates.  Please ensure you check your email regularly. At University Health Network (UHN), artificial intelligence technologies may be used to assist in the screening, assessment, and selection of candidates for this position. Please be advised that a Criminal Record Check may be required of the successful candidate. Should it be determined that any information provided by a candidate be misleading, inaccurate or incorrect, UHN reserves the right to discontinue with the consideration of their application. UHN is an equal opportunity employer committed to an inclusive recruitment process and workplace. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their

Postdoctoral Research Fellow in Cytosolic Nucleic Acid Biology

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Job TitlePostdoctoral Research Fellow in Cytosolic Nucleic Acid Biology LocationSFU Burnaby Campus, Burnaby BC, Canada SalaryBetween $50,000 – $60,000/yr plus benefits commensurate with experience and qualifications; will increase with fellowship awards. Position DetailsFull-time position for one year with the expectation of renewal based on satisfactory performance and continual funding. Starts as soon as possible. Key Responsibilities Design and perform experimental studies using multiple types of immortalized human cell lines. Design and perform fixed and live-cell fluorescence microscopy studies, including confocal and high-content techniques, to study nucleic acid membrane escape. Collaborate with a cryo-electron microscopy core facility to collect and analyze electron microscopy data. Maintain accurate records of experimental results and reagents produced. Prepare manuscripts, reports, and presentations to relay research findings to both internal and external colleagues and stakeholders. Perform conventional tasks required for the successful completion of the above tasks (molecular biology, genetic manipulation, etc). Train and mentor undergraduate and graduate trainees assigned to assist in the tasks. Occasionally assist on other research projects in the laboratory. Apply for applicable research fellowship support. Required Qualifications PhD in Cell Biology, Biochemistry, Molecular Biology, or other related fields. Extensive experience in mammalian cell culture and fluorescence microscopy. Demonstrated record of lead author peer-reviewed publications arising from doctoral or postdoctoral research. Excellent verbal and written communication skills. High level of critical and analytical ability. Demonstrated ability to independently design, execute, and troubleshoot research projects. Assets Expertise in genome stability, delivery of nucleic acid therapeutics, or innate immune signaling pathways. Experience with live-cell imaging, high content microscopy, and/or cryo-electron microscopy (training opportunities will be provided). Computational experience, especially associated with microscopy data processing. A strong track record of mentorship of junior colleagues. Teamwork and collegiality. How to ApplySubmit the following documentation as a single PDF to dheva_setiaputra@sfu.ca and include “PDF in Cytosolic Nucleic Acid Biology” in the subject line: A cover letter describing your research interests and suitability to the position. An up-to-date CV. Contact information for three references. Application DeadlineApplicants will be screened immediately and will continue until the position is filled.  

Scientific Assistant – in the Department of Microbiology and Molecular Medicine

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Job Description The Faculty of Medicine at the University of Geneva benefits from an enriching multicultural dynamic to which it contributes through its influence within the framework of the mandates it has given itself: teaching, research and its partnership with the Geneva University Hospitals (HUG). The Department of Microbiology and Molecular Medicine at the Faculty of Medicine manages a dozen research groups and four affiliated clinical groups. To strengthen its dynamic team, the Department of Microbiology and Molecular Medicine is seeking a: Scientific Assistant (1-50%) The main research areas of the genomic research laboratory address various clinical problems related to bacterial colonization of the human body, using metataxonomic , metagenomic and genomic approaches based on next generation sequencing (NGS). Within the genomic research laboratory of the Department of Microbiology and Molecular Medicine, the main responsibilities of this position are: Analyze metagenomic and genomic sequencing data (from read processing to statistical analysis);  Interpret the results and provide graphical representations; Write clinical reports; Participate in writing articles; Update the laboratory databases; Train interns in bioinformatics; Manage orders and stock (hardware and software).  Required qualifications and skills You have a Master’s degree in bioinformatics and relevant additional training, or training deemed equivalent, and can claim several years of successful experience and in-depth technical knowledge in metagenomics / metataxonomics; You have already analyzed Illumina and Nanopore sequencing data; You are proficient in the characterization of bacterial genomes (assembly, search for AMR, virulence factors, SNPs…); You are proficient in one or more programming languages ​​(Python, R…) and have already developed a pipeline for the analysis of genomic and/or metagenomic sequencing data; You have good analytical, synthesis and writing skills in French and English; Prior knowledge of HUG, UNIGE and clinical research would be an asset. Entry into office August 1, 2026 Contact If you fit the above description, we would be very happy to receive your application file (cover letter, CV, certificates, diplomas) which must be submitted exclusively online by clicking on the “Apply now” button below . Additional information Fixed-term contract of 9 months at 50%.  Apply Now

PhD Position in Microbial Physiology and Biotechnology: Physiology and Ecology of Methanogens

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Mission The Microbial Physiology and Resource Biorecovery Laboratory (MICROBE), led by Dr. Wenyu Gu at the Swiss Federal Institute of Technology Lausanne (EPFL), invites applications for a fully funded PhD position in Microbial Physiology. We are seeking a highly motivated and talented PhD student to join our team at the Institute of Environmental Engineering. The successful candidate will conduct cutting-edge research in applied and environmental microbiology, with a focus on the physiology and genetic regulation of methane-producing archaea: methanogens. These microorganisms play a central role in the global carbon cycle by mediating the terminal steps of organic matter degradation in anoxic environments. Their activity serves as a critical gatekeeper of energy flow in oxygen-depleted ecosystems, including wetlands, sediments, animal digestive tracts, and anaerobic digesters, where they catalyze the final stages of anaerobic carbon mineralization. Main duties and responsibilities The research will investigate how methanogens respond to dynamic environmental conditions and interact with other members of microbial communities, advancing our understanding of the ecological mechanisms governing methane production and informing future biotechnological applications. The project will combine a range of experimental and computational approaches, including high-throughput sequencing and bioinformatics, microbial isolation and cultivation, physiological characterization of gas-utilizing microorganisms, and co-culture and community function analyses. The PhD candidate will collaborate closely with other PhD students and postdoctoral researchers, both within the laboratory and across EPFL’s international research network. Profile Master’s degree in environmental engineering, microbiology, chemical engineering, or a related discipline. Demonstrated research experience through a master’s thesis, publications, or equivalent research projects. Prior experience in wet-lab microbiology and/or bioinformatics is an advantage. Strong communication and scientific writing skills in English. Ability to work effectively in a collaborative and international research environment. We offer Mentoring and support for professional and personal development. A stimulating, multicultural research environment with access to state-of-the-art facilities. Opportunities for interdisciplinary collaboration and international networking. A world-class training environment within the ETH Domain. Informations Start date: Flexible. Contract duration: One-year contract, renewable annually for up to four years. To apply, please follow the instructions provided in the application portal linked below. Please prepare the following application materials: Motivation letter. Detailed curriculum vitae (CV). Contact information. Names and contact details of three references who are willing to provide recommendation letters. Applications will be reviewed on a rolling basis, and the position will remain open until a suitable candidate has been identified and the position has been filled. Apply Now

Application Scientist position for Spatial / Single Cell Genomics Expert

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The Genomics Facility Basel (GFB) is a central academic technology platform jointly operated by the University of Basel and the Department of Biosystems Science and Engineering (D‑BSSE) of ETH Zurich. The facility supports cutting-edge life science research across campus boundaries and provides services and expertise to associated institutions, including the Botnar Institute of Immune Engineering (BIIE), as well as external academic and industrial partners.Please enter text here Project background GFB offers access to state-of-the-art genomics technologies and actively drives innovation in next-generation sequencing, single-cell and spatial genomics, and emerging multi-omics approaches. To strengthen our R&D and user support activities, we are seeking a highly motivated PhD-level Application Scientist to join our team. Job description Evaluation, implementation, and benchmarking of emerging genomics technologies within an academic core facility environment Scientific and technical support of user projects, including experimental design, method selection, and troubleshooting, in close collaboration with researchers from the University of Basel, ETH Zurich, and associated institutes Research and development of novel workflows, with a strong focus on establishing scalable, robust, and high-throughput approaches in: Library preparation technologies Single-cell sequencing Spatial transcriptomics Multi-omics strategies Optimization, validation, and documentation of methods and standard operating procedures (SOPs) Active participation in internal R&D projects, technology pilots, and collaborative research initiatives Communication of new technologies and results through user consultations, training sessions, presentations, and written documentation Profile PhD in biology, molecular biology, genomics, bioengineering, or a related life science discipline Strong hands-on experience with modern genomics and molecular biology techniques, particularly next-generation sequencing. Demonstrated experience in one or more of the following areas: Single-cell genomics Spatial transcriptomics Multi-omics workflows High-throughput library preparation methods A strong academic mindset with curiosity for technology development and method optimization Ability to work independently while contributing effectively within a collaborative, service-oriented academic environment Committed to excellence within a collaborative team, focusing on shared success and high-quality service delivery in an academic setting Excellent organizational, analytical, and problem-solving skills Practical experience in working in an NGS core facility is an advantage. Fluent oral and written communication skills in English are essential We offer An intellectually stimulating position within a leading academic technology platform at the interface of research, service, and innovation The opportunity to actively shape and establish new genomics technologies and workflows Daily interaction with a diverse and highly interdisciplinary research community Access to state-of-the-art instrumentation and evolving genomics platforms Attractive employment conditions and opportunities for professional development A workplace in Basel, a major international hub for life sciences and biomedical research chevron_rightWorking, teaching and research at ETH Zurich We value diversity and sustainability In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate-neutral future. Curious? So are we. We look forward to receiving your online application with the following documents: A motivation letter outlining your interest in genomics technologies and academic service platforms Curriculum vitae Contact information for referees (or reference letters, if available)/work certificates Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered. Further information about the Genomics Facility Basel can be found on our website. Questions regarding the position should be directed to Dr. Christian Beisel: christian.beisel@bsse.ethz.ch (no applications). We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence. For recruitment services the GTC of ETH Zurich apply. Application Form

Recruitment for Scientific project assistant predoctoral

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The University of Vienna is a community of almost 11,000 individuals, including approximately 7,700 academic staff members, who passionately pursue answers to the profound questions that shape our future. They represent individuals driven by curiosity and a relentless pursuit of excellence. With us, they find the space to try things out and unfold their potential. Are you inspired by their passion and determination? We are currently seeking a/an Scientific project assistant predoctoral  50 Faculty of Life Sciences   Job vacancy starting: 01.10.2026 | Working hours:  30,00  | Classification CBA: §48 VwGr. B1 Grundstufe (praedoc)  Limited contract until:  Job ID: 5930 Explore and teach at the University of Vienna, where more than 7,500 academics thrive on curiosity in continuous exploration and help us better understand our world. Does this sound like you? Then join our accomplished team! Your personal sphere of influence: We are a young and enthusiastic team at the Department of Pharmaceutical Sciences that is focused on developing new treatments against drug resistant and metastatic states of lung cancers by working at the interface of, medicinal chemistry, chemical methodology development, cancer chemical biology and (chemo)proteomics. The project is strongly connected to the key goal of the group to study phenotypic plasticity with regard to cancer progression, hydrogen peroxide signaling and ferroptosis. For more information, visit: https://konradlab.univie.ac.at/  Your future tasks: The most commonly used techniques for the project are chemical synthesis as well as the analysis of the produced compounds and their reactivity. To perform chemical syntheses, we expect experience with standard inert-atmosphere techniques such as Schlenk line and glovebox set-ups. For compound analysis, NMR, HRMS, HPLC, LC-MS and UV-vis are frequently used techniques. The reactivity of chemical probes will be determined through reaction kinetics measurements. We encourage students to apply who have experience with most of these methods and are excited to expand their skillset with the approaches that they are not yet familiar with. Programming skills in python and R with experience in statistical data analysis, especially with large omics datasets, are a strong bonus. This is part of your personality: You have a completed Master’s degree (or equivalent) with a focus in: Pharmaceutical Sciences Drug Development Chemistry Biochemistry Chemical Biology Experience in synthetic organic / medicinal chemistry and a passion for drug discovery A deep interest and an enthusiasm for scientific work A critical and analytical mind Ability to work responsibly, reliably, diligently and independently perform experiments Ability to work in a multidisciplinary team within the group and with external collaborators A passion for training colleagues and students in the laboratory Experience in the most commonly employed techniques in the laboratory (see “Your future tasks” section)) Programming skills in python and R with experience in statistical data analysis are an advantage. What we offer: Work-life balance: Our employees enjoy flexible working hours and can partially work remotely.  Inspiring working atmosphere: You are a part of an international academic team in a healthy and fair working environment. Good public transport connections: Your workplace is easily accessible by public transport. Internal further training & Coaching: Opportunity to deepen your skills on an ongoing basis. There are over 600 courses to choose from – free of charge. Fair salary: EUR 2.832,08 gross (for a 30-hour-contract/14 salaries per year), the salary increases after 3 years of predoc-experience Equal opportunities for all: We welcome every additional/new personality to the team! It is that easy to apply: With your scientific curriculum vitae  Master Degree  /  Diploma certificate Other relevant certificates With a motivation letter summarizing your research interests Reference list  Via our  job portal/ Apply now –  button If you have any questions, please contact: David Benjamin Konrad   david.benjamin.konrad@univie.ac.at We look forward to new personalities in our team! The University of Vienna has an anti-discriminatory employment policy and attaches great importance to equal opportunities, the advancement of women and diversity. We place particular emphasis on enhancing women’s representation among the academic and general university staff, particularly in leadership roles, and therefore expressly encourage qualified women to apply. Given equal qualifications, preference will be given to female candidates. Apply Now

Head of Biobank (f/m/d)

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At the St. Anna Children’s Cancer Research Institute (St. Anna CCRI), science and clinical care are inseparably linked by a shared mission: improving the lives of children with cancer. This open role builds on an existing, actively used biobank infrastructure, embedded in routine diagnostics and numerous ongoing clinical trials.  We are now seeking an exceptional Head of Biobank to strategically modernize, consolidate, and further integrate this long‑standing biobank into a state‑of‑the‑art, certified infrastructure, including a sustainable digital database linked to clinical, diagnostic, and research data. This position is open to candidates at different career stages. This is a rare opportunity to lead a state-of-the-art biobank that directly fuels precision oncology, cutting edge multi-omics research, and clinical innovation, turning high quality biospecimens into tangible breakthroughs for patients. Key responsibilities Lead and further develop a certified biobank: Consolidate and modernize a long‑standing biospecimen collection, covering collection, processing, storage, and governance, and integrate it into a modern, database‑driven infrastructure linked to clinical, diagnostic, and research data. Strategic development & quality excellence: Define the biobank’s long‑term strategy, infrastructure, and workflows, ensuring compliance with regulatory, ethical, biosafety, and ISO quality standards. Clinical trial‑embedded biobanking: Oversee biospecimen acquisition, processing, and storage within numerous ongoing national and international clinical trials, respecting study‑specific regulatory requirements, material types, and defined time points. Robust governance & lifecycle management: Ensure full sample lifecycle governance, including consent, traceability, documentation, data integrity, and transparent access processes for researchers. Digital & infrastructural innovation: Lead the integration of existing biobank collections into a modern database environment, including metadata harmonization, linkage to clinical, diagnostic, and research data, and implementation of query interfaces for internal and external scientific users. Institutional & translational collaboration: Act as a central interface to the clinical diagnostics laboratory Labdia (St. Anna CCRI subsidiary), Precision Oncology, the St. Anna CCRI Clinical Trials Unit, pathology partners, and research groups to support translational research pipelines. Leadership, visibility & sustainability: Build and lead a high‑performing team, represent the biobank in national and international networks, and secure funding to ensure long‑term sustainability. Required Qualifications PhD, MD/PhD, or equivalent degree in biology, biomedical sciences, pathology, or a related discipline. Several years of experience in biobanking, biospecimen management, laboratory quality systems, and ISO accreditation processes. Experience in establishing, optimizing, or managing laboratory infrastructures or service platforms is an advantage. Expertise in digital pathology, database systems, metadata structures, and modern sample lifecycle management platforms. Strong leadership capabilities with demonstrated team management, problem‑solving strengths, and scientific judgement. Experience collaborating with pathology, clinical teams, IT, clinical trials units, and diagnostic partners. Familiarity with ethical, legal, and regulatory frameworks for human biospecimen handling. Excellent communication and documentation skills within interdisciplinary scientific environments. Ability to thrive in a dynamic, collaborative, and technology‑driven setting. Fluent German and English required. Our offer Strong institutional commitment & sustainable funding: Long‑term investment and stable internal funding to establish and operate a certified, state‑of‑the‑art biobank as a core institutional infrastructure, complemented by support for third‑party funding acquisition. Embedded translational ecosystem: Close integration with clinical care, precision oncology, diagnostics, clinical trials, and advanced multi‑omics and digital pathology platforms. Professional institutional support: Well‑established support structures for quality management, IT, grant management and other internal support functions. Attractive employment conditions: Competitive remuneration, flexible working arrangements, and tailored onboarding support for international candidates. Mission‑driven culture & location: A collaborative, purpose‑driven institute dedicated to improving outcomes for children with cancer, based in Vienna, offering excellent quality of life and a strong biomedical ecosystem. Compensation: The minimum annual gross salary for this position is € 73.000.- (all in), with the possibility of higher compensation depending on qualifications and experience. Contract terms: The initial appointment is for 2 years. Subject to a positive evaluation, a rolling tenure with regular evaluations is foreseen, reflecting the institute’s long‑term strategic commitment to this role. Who we are One of Europe’s leading institutions in the field of pediatric oncology, St. Anna Children’s Cancer Research Institute (St. Anna CCRI) investigates the biological foundations of cancer in children and adolescents. For almost 40 years, our multidisciplinary teams have been committed to developing innovative diagnostic approaches and personalized treatments aimed at further improving young patients’ chances of cure. In close collaboration with the St. Anna Children’s Hospital and both national and international partners, we combine scientific excellence with clinical relevance. We stand for responsible research, transparency, and sustainable knowledge building. As an employer, we offer a state-of-the-art research environment, opportunities for professional development, as well as a workplace culture that embraces diversity and appreciation. Work where it really matters and contribute to science that makes a difference. St. Anna CCRI is an equal opportunity employer. We value diversity and are committed to providing a work environment of mutual respect to everyone without regard to race, colour, religion, national origin, age, gender identity or expression, disability, or any other characteristic protected by applicable laws, regulations and ordinances. Find more information here: https://ccri.at/. Your application We are looking forward to your application! Applications will be reviewed on a rolling basis until the position is filled. Please submit the following documents:      • Curriculum Vitae (including full publication list)      • List of up to five most important publications with a short comment explaining the relevance of the paper and your contribution      • Funding track record      • Names and contact details of at least three references      • Description of your previous experience relevant to biobanking, including operational, technical, or strategic responsibilities In case of questions please contact us at faculty-recruiting@ccri.at. Your recruiting process Our recruitment process is designed to ensure a fair, transparent, and rigorous evaluation. It includes the following steps: Initial screening and pre‑selection Virtual interviews with the Scientific Directors On‑site hearing Offer & final negotiations Apply Now

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