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Ilaira Piazza

3 months ago

PhD Student in Proteomics-Driven Modeling of Protein Dynamics (Data-Driven Life Science) Stockholm University in Sweden

Degree Level

PhD

Field of study

Biochemistry

Funding

Available

Deadline

Expired

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Country

Sweden

University

Stockholm University

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Keywords

Biochemistry
Computer Science
Machine Learning
Molecular Biology
Chemistry
Biomedical Engineering
Deep Learning
Biology
Structural Biology
Computational Biology
Mass Spectrometry
Medical Science
Protein Dynamics
Statistics
Bioinformatic

About this position

The Department of Molecular Biosciences, The Wenner-Gren Institute (MBW) at Stockholm University is internationally recognized for its research in molecular cell biology, integrative biology, and infection and immunobiology. The institute comprises 30 research groups and a vibrant community of 180 researchers, including 65 PhD students. This PhD position is part of the SciLifeLab and the Wallenberg National Program for Data-Driven Life Science (DDLS), offering a unique interdisciplinary environment at the interface of structural proteomics, protein biophysics, and machine learning.

The project focuses on proteomics-driven modeling of protein dynamics, aiming to integrate experimental data with generative deep-learning models to better understand protein conformational ensembles. While advances like AlphaFold have revolutionized protein structure prediction, most models remain limited to static representations. This research seeks to overcome these limitations by using structural proteomics methods to measure protein accessibility and flexibility, guiding and benchmarking machine-learning models that predict protein conformational states and structural ensembles.

The successful candidate will join the Piazza laboratory, renowned for its expertise in quantitative proteomics and proteome-wide analysis of protein structural changes, and collaborate closely with Prof. Arne Elofsson’s group, which specializes in computational structural biology, protein modeling, and machine learning. The student will have access to large-scale datasets, state-of-the-art mass spectrometry infrastructure at SciLifeLab, and high-performance computing resources at Stockholm University and national Swedish facilities.

Training will encompass quantitative proteomics, structural biology, computational biology, machine learning, data integration, and scientific communication. The DDLS Research School provides additional opportunities for national courses, seminars, and networking within data-driven life science. The project is expected to yield methodological advances and new biological insights into protein regulation in cells.

Applicants must meet general and specific entry requirements, including a second-cycle degree or equivalent, documented knowledge in relevant fields, and proficiency in English. Desired skills include programming (Python, R), experience with proteomics, mass spectrometry, protein structure analysis, molecular dynamics, deep learning, or bioinformatics. Analytical thinking, scientific curiosity, motivation for interdisciplinary research, and the ability to collaborate in an international environment are essential.

The position is full-time, fixed-term for four years, with annual renewal. Funding is provided by the DDLS and Knut and Alice Wallenberg Foundation. Stockholm University is committed to equal opportunities and a discrimination-free workplace. The expected start date is October 2026, and the application deadline is July 13, 2026.

To apply, submit your application via Stockholm University’s recruitment system, including a personal letter, CV, and all required documents. For further information, contact Dr. Ilaira Piazza at [email protected]

Funding details

Available

What's required

Applicants must have completed a second-cycle degree or equivalent courses totaling at least 240 higher education credits, with 60 credits in the second cycle, or have equivalent knowledge. Documented knowledge in molecular biosciences, biochemistry, proteomics, structural biology, bioinformatics, computational biology, machine learning, or related areas is required. Analytical and creative thinking, scientific curiosity, motivation for interdisciplinary research, initiative, independence, and ability to collaborate in an international environment are essential. Written and oral proficiency in English is required. Programming skills in Python, R, or another relevant language are desirable. Experience with proteomics, mass spectrometry, protein structure analysis, molecular dynamics, deep learning, or bioinformatics is advantageous but not required. Experience with data analysis of other -omics data is valuable.

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