项目介绍

2026年4月30日

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Contextual modelling of IDPs in cancer hubs – from proxiomes to direct interactions: A DDLS PhD student position at LiU in collaboration with University of Toronto

At Linköping University, we are announcing the position as DDLS PhD student in “Data driven cell and molecular biology”. This field covers research that fundamentally transforms our knowledge about how cells function by peering into their molecular components in time and space, from single molecules to native tissue environments.

Specifically, this project aims to exploit mass spectrometry proxiome data to leverage our knowledge on how intrinsically disordered proteins (IDPs) bind and regulate critical protein hubs. We will do this by developing novel pipelines for predictive interaction modelling, complemented by collaborative validation through cellular and biophysical approaches. This integrated strategy will enable structural and dynamic characterisation of IDP interactions based on their native cellular context, opening novel modes to target critical interactions in cancer.

Your work assignments

As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or other departmental duties, up to a maximum of 20 per cent of full-time.

In this position, your task will be to enhance state-of-the-art predictive modelling of IDP interactions by actively integrating proximity profiling data from biotinylated interactomes assayed by mass spectrometry (BioID). Highly dynamic intrinsically disordered regions (IDRs) are present in ~70% of proteins in the human proteome, and adopt conformational ensembles rather than fixed 3D structures, both alone and in the context of complexes. Despite recent immense progress in in-silico structural proteomics (2024 Nobel Prize to Baker, Hassabis, Jumper), the amount of experimental data on such complexes is still not sufficient to train AI protocols to reliably predict IDP interactions.

Our approach will leverage data on regulatory protein hubs in cancer where we have direct access to experimental validation and will be directly applicable to other proteins with relevant deposited data. The experimental BioID technique is high-throughput and uniquely identifies both structural and transient/dynamic protein interactions within cells, providing insights into dynamic biology in-vivo. However, BioID alone cannot distinguish direct interactions from proxymediated, nor can it resolve structural details of these interactions. To address these limitations, we will develop novel pipelines for predictive molecular-resolution interaction modelling with BioID data, with resulting models to be used as hypothesis-driving in collaborative experimental labs at LiU, KI and University of Toronto. This integrated strategy will enable structural and dynamic characterisation of IDP interactions based on their native cellular context, opening novel modes to target critical IDP interactions in cancer.

Your qualifications

You have graduated at Master’s level in natural, medical or engineering science or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses. Alternatively, you have gained essentially corresponding knowledge in another way.

It is highly meriting for the position if you can say yes to some of the points below,:

• Proficiency in programming languages, preferably Python.
• Knowledge of AI and machine learning techniques
• Experience in AI applications for structural bioinformatics or related areas.
• Familiarity with the AlphaFold platform and its applications in protein structure prediction.
• Experience with BASH and the command line.
• Background in structural biology, molecular modeling, protein dynamics, and understanding of ensembles.
• Experience with molecular modeling and simulation software, such as GROMACS, NAMD, or Rosetta.

The successful applicant should have a profound interest in pursuing interdisciplinary Life Science through collaborative interactions. Merits include active participation in interdisciplinary research teams, whether academic or industrial. Scientific curiosity and the ability to think independently are essential personal qualities in a candidate. You will be expected to engage with colleagues and cooperate in supporting the activities of the research group. You must also have excellent oral and written communication skills in English. You should enjoy working as part of a team, and be willing to learn from your co-workers and to share your knowledge and experience with them in return.

A Letter-of-intent should be attached, describing your interest and qualifications and how you meet the qualifications asked for this position.

Your workplace

You will be employed at the Department of Physics, Chemistry and Biology (IFM) at Linköping University, where its divisions of chemistry and bioinformatics conduct research and education in protein science, structural bioinformatics and structural biology. The PhD student will follow the postgraduate program in bioinformatics and will carry out research stays at the University of Toronto as part of the PhD project.

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. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life scientists and to create globally leading computational and data science capabilities in Sweden. The program is funded with a total of 3.3 billion SEK over 12 years from the Knut and Alice Wallenberg (KAW) Foundation.

In 2026 the DDLS Research School will be expanded with the recruitment of 25 academic and 7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and biology of infection. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/

The future of life science is data-driven. Will you be part of that change? Then join us in this unique program!

The employment

When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each faculty is available at Doctoral studies at Linköping University

The employment has a duration of normally four years’ full-time equivalent. Extension of employment up to five years is based on the degree of teaching and institutional assignment. Further extensions may be granted in exceptional circumstances. You will initially be employed for one year, after which your employment will be renewed for a maximum of two years at a time, depending on your progress through the study plan. 

Starting date by agreement.

Salary and employment benefits

The salary of PhD students is determined according to a locally negotiated salary progression.

More information about employment benefits at Linköping University is available here.

Union representatives

Information about union representatives, see Help for applicants.

Application procedure

Apply for the position by clicking the “Apply” button below. Your application must reach Linköping University no later than the 28^th of May 2026.

Applications and documents received after the date above will not be considered.

We welcome applicants with different backgrounds, experiences and perspectives – diversity enriches our work and helps us grow. Preserving everybody’s equal value, rights and opportunities is a natural part of who we are. Read more about our work with: Equal opportunities.

We look forward to receiving your application!