Arbetsbeskrivning

We are looking for a motivated PhD student to join us in a unique, collaborative project between our Affinity Ligand Design team at Cytiva and the Elofsson group at Stockholm University, where we will use machine learning methods to develop affinity ligands. These methods have been transformative for protein design, allowing generation of novel proteins which can suit a precise need. In this 4 year project, funded by the DDLS program, we aim to develop AI-based tools in design of affinity ligands, such as the prediction of binding interactions between proteins.

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 2025, the DDLS Research School will be expanded with the recruitment of 19 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 Elofsson group is located at the Science for Life Laboratory. Elofsson has worked on protein structure predictions for more than two decades and on various techniques using machine learning and other computational techniques. Some of his most important contributions to this work are the methods he has developed to improve the prediction of membrane protein, protein structures and protein interactions. The group comprises four PhD students, one postdoc, and one senior researcher. For recent publications, see here: https://archive.bioinfo.se/papers/

Cytiva’s Affinity Ligand Design team is a small unit of our company, located in the Karolinska campus, and is responsible for discovering and designing new affinity purification ligands and solutions for the next generation of biopharmaceuticals. We consist of about 15 experts in the field of protein engineering, protein production, affinity ligand design and characterization, and machine learning for protein design.

This unique PhD position is a 4-year collaborative project where you will work at the Cytiva Solna and Elofsson lab environments, both located at the Solna Campus. Upon successfully completing the 4-year project, you will obtain a PhD in Bioinformatics from Stockholm University.

Requirements:

• An MSc, including a thesis of at least 30 hp in Biotechnology, Bioinformatics, or related fields.
• English as a working language, with Swedish as a strong merit.
• Experience in Python programming.
• Experience with machine learning methods, bioinformatics, and data science.
• Familiarity with generative AI tools for protein design and protein language models.
• Knowledge of protein structure, function, and interactions.
• It is a merit if you have knowledge of protein engineering, characterization and/or purification methods.
• A valid EU work permit is required.

Please submit your application no later than June 29th. For questions regarding the role, please contact Professor Arne Elofsson at [email protected] or the Project Manager at Cytiva, Sarah McComas at [email protected].

Join our winning team today. Together, we’ll accelerate the real-life impact of tomorrow’s science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life.

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