PhD position in Proteomics-driven modeling of protein dynamics

The Department of Molecular Biosciences, Wenner-Grens Institute (MBW ) conducts experimental basic research in molecular cell biology, integrative biology and infection and immunobiology. The research environment is characterized by a modern and advanced methodology and has a strong international profile. MBW is one of the larger departments within the Faculty of Science at Stockholm University with just over 30 research groups and approximately 180 employees, of which 65 are doctoral students. More information about us can be found at: Department of Molecular Biosciences, Wenner-Grens Institute

Project description

Proteomics-driven modeling of protein dynamics

We are looking for a highly motivated PhD student for a DDLS-funded project at the interface between structural proteomics, protein biophysics and machine learning. The position is part of SciLifeLab and the graduate school within the Wallenberg National Program for Data-Driven Life Science (DDLS), within the research area Cell and Molecular Biology. The PhD student will use and develop both computational and experimental methods.

Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels – from molecular structures and cellular processes to human health and global ecosystems. SciLifeLab and the Wallenberg National Program for Data-Driven Life Science (DDLS) aim to recruit and train the next generation of data-driven life scientists and to build world-leading competence in computational and data science in Sweden. The program is funded with a total of 3.3 billion SEK over 12 years by the Knut and Alice Wallenberg Foundation.

In 2026, the DDLS graduate school will be expanded by recruiting 25 academic and 7 industrial doctoral students. Over the course of the program, more than 260 doctoral students and 200 postdoctoral fellows will be part of the graduate school. The DDLS program covers four strategic research areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, and epidemiology and infection biology. For more information, see the Scilifelab website .

Proteins are dynamic molecules whose biological functions are governed not only by their folded structures, but also by conformational changes induced by ligand binding, cofactors, metabolites, stress, or post-translational modifications. Although modern deep learning methods such as AlphaFold have revolutionized protein structure prediction, most current models still describe proteins primarily as static structures and do not fully capture the conformational ensembles that underlie protein function.

This PhD project aims to address this limitation by integrating experimental data with modern generative deep learning models for protein conformational dynamics. The project will use structural proteomics methods that measure local protein accessibility and flexibility across thousands of proteins under native conditions. These experimental data will be used to guide, train, and evaluate machine learning models that predict protein conformations and structural ensembles.

The project builds on the extensive expertise of the Piazza laboratory in quantitative proteomics and proteomic analysis of protein structural changes. The doctoral student will work closely with the group led by Professor Arne Elofsson at Stockholm University, who brings expertise in computational structural biology, protein modeling and machine learning. The project thus offers a unique interdisciplinary educational environment that combines experimental mass spectrometry-based proteomics with AI-driven modeling of protein structures.

The PhD student will have access to large-scale datasets generated in the Piazza laboratory, public datasets in structural proteomics, state-of-the-art mass spectrometry infrastructure at SciLifeLab, as well as high-performance computing resources at Stockholm University, SciLifeLab and national Swedish infrastructure. The project is expected to lead to both methodological advances and biological insights into how protein conformational states are regulated in cells.

The doctoral student will be part of a multidisciplinary and international research environment and will receive training in quantitative proteomics, structural biology, computational biology, machine learning, data integration and scientific communication. As part of the DDLS graduate school, the student will also participate in national courses, seminars and networking activities in data-driven life science.

Planned start date is October 2026.

The future of life sciences is data-driven. Do you want to help shape that development? Welcome to become part of this unique program!

The dissertation work will be conducted within the framework of this project.

Eligibility requirements

To be admitted to doctoral studies, the applicant must have basic and specific eligibility requirements. The eligibility requirements must be met by the application deadline.

You have basic eligibility if you have completed a degree at advanced level, or have completed course requirements of at least 240 higher education credits (ECs), of which at least 60 ECTS credits are at advanced level, or have otherwise acquired essentially equivalent knowledge within or outside the country.

Specific eligibility requirements are described in the general curriculum for doctoral education in the subject.

Selection

Selection of applicants is made based on their ability to benefit from postgraduate education. Criteria used to assess this ability are:

• Documented knowledge in relevant areas such as molecular bioscience, biochemistry, proteomics, structural biology, bioinformatics, computational biology, machine learning or related areas.
• analytical and creative thinking
• Scientific curiosity and motivation for interdisciplinary research.
• Initiative and independence.
• Ability to collaborate in an international and interdisciplinary research environment.
• Good ability to express oneself verbally and in writing in English.

The applicant should also have:

• A strong interest in protein science, proteomics, structural biology, computational biology or machine learning.
• A solid background in molecular biology, biochemistry, bioinformatics, computational biology, computer science, physics, chemistry or related fields.
• Motivation to work in an interdisciplinary project that connects experimental biological data to computational modeling.
• Programming skills in Python, R or other relevant programming language.
• Interest in machine learning, statistical modeling, structural bioinformatics, or analysis of large-scale biological datasets.
• Experience in proteomics, mass spectrometry, protein structure analysis, molecular dynamics, deep learning or bioinformatics is an advantage but not a requirement. Experience in analysis of other types of -omics data is also valuable.
• Curiosity, analytical thinking and willingness to learn new experimental and computational methods.

A strong interest in interdisciplinary research and the integration of experimental proteomics with data-driven modeling is essential for employment.

Admission procedure for doctoral education at Stockholm University.

About the employment

We offer a fixed-term employment as a doctoral student in accordance with Chapter 5 of the Higher Education Ordinance (1993:100). The employment period may not be longer than the equivalent of four years of full-time doctoral education. As a doctoral student, you will primarily devote yourself to your own doctoral education, but the employment may include work with education, research and administration to a limited extent (maximum 20%).

A new appointment as a doctoral student is valid for a maximum of one year, and the appointment is then renewed for a maximum of two years at a time.

Stockholm University strives to be a workplace that is free from discrimination and provides equal rights and opportunities for everyone.

Contact

Further information is available from Dr. Ilaria Piazza, Ilaria.piazza@su.se .

Application

You apply for the doctoral position via Stockholm University’s recruitment system. Attach a cover letter and CV as well as the attachments requested in the application form. As an applicant, you are responsible for ensuring that the application is complete in accordance with the advertisement and that it reaches the university by the application deadline.

Instructions for applicants can be found on the website: applying for a job .

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