Algorithm Researcher Position - Virtual Patient Engine in Heidelberg bei BioMed X GmbH

About BioMed X

BioMed X is an independent research institute located on the campus of the University of Heidelberg in Germany with a world-wide network of partner locations. Together with our partners, we identify big biomedical research challenges and provide creative solutions by combining global crowdsourcing with local incubation of the world’s brightest early-career research talents. Each of the highly diverse research teams at BioMed X has access to state-of-the-art research infrastructure and is continuously guided by experienced mentors from academia and industry. At BioMed X, we combine the best of two worlds - academia and industry - and enable breakthrough innovation by making biomedical research more efficient, more agile, and more fun.

About the Team

The goal of team ‘Next Generation Virtual Patient Engine for Clinical Translation of Drug Candidates’ (VPE) led by Dr. Douglas McCloskey is to develop a versatile computational platform that can predict the efficacy of first- or best-in-class drug candidates in virtual patient populations at an unprecedented accuracy, thereby addressing one of the most critical bottlenecks of the pharmaceutical industry today: a 90% failure rate of new drug candidates during clinical development. In partnership with Sanofi the VPE team will develop innovative artificial intelligence methods to build the virtual patient platform. As a proof-of-concept, the initial platform will focus on chronic immune-mediated diseases such as atopic dermatitis (AD) and inflammatory bowel disease (IBD), where new medication that can address patient heterogeneity is needed.

The Position

We are looking for highly enthusiastic researchers to broaden our think-tank with their intellectual power and technical excellence. The ideal candidate would have a PhD degree or equivalent in artificial intelligence or related fields, and a strong background in modern deep learning techniques.

Required Skills

• Proficiency in using and theoretical understanding of modern deep learning methods including deep generative modeling, deep graph modeling, and foundation model development and transfer learning.
• Experience in developing recommendation engines using static or temporal knowledge graphs, learned simulators of physical, biological, or other temporal data sources, and/or active learning or causal discovery.
• Proficiency in using modern deep learning libraries including PyTorch; using version control with Git, Docker containers, and Anaconda; proficiency in using code management best practices such as unit testing, linting, and documentation; orchestrating machine learning experiments using cloud computing environments; and using continuous integration and deployment (CI/CD) frameworks.
• While a background in life sciences is not a prerequisite for the position, a strong interest in applying modern machine learning to solve problems in biology and medicine will be needed.
• Independent thinking
• Experienced to work in interdisciplinary teams

Additional Preferred Skills

• While a background in life sciences is not a pre-requisite for the position, and the team would support the required domain knowledge during the project, experience working with -omics data and in particular single-cell sequencing data, clinical data such as electronic health records, and traditional differential equation solvers and/or generative models for synthetic/simulated data generation is encouraged.
• Understanding of AGILE methodologies.

What We Offer

The post is offered for a limited term until June 30, 2028.

• Flexible working hours and hybrid working location
• Access to a vast network in science and industry. The team will be working closely with our industry partner Sanofi, various high-profile academic partners, and industry-academia consortiums during the course of the project.
• Opportunities to publish in top academic journals and present at top academic and industry conferences.
• Training in how scientific teams take a high-risk and high-reward idea from development to early-stage productization using AGILE methodologies.
• International, diverse, and positive work atmosphere that fosters personal and professional growth.
• Job ticket, sponsored fitness contract, complimentary fresh fruit, soft drinks, and chocolate team recognition events, free German lessons, complimentary Coursera courses, etc.

The position is sponsored by Sanofi.

Candidates Are Requested to Submit

• 1-page cover letter explaining the reasons of interest to join our team and contributions you would make to the t