Bioinformatician Position (all genders) - Virtual Patient Engine

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 Team VPE

The goal of team VPE lead 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 Ph.D. degree or equivalent in bioinformatics, computational biology, or biomedical artificial intelligence.

Required skills

• Proficiency in accessing and working with biomedical knowledge graphs and databases to apply knowledge-driven mathematical modelling and/or data-driven statistical modelling techniques to chemical reaction prediction and retrosynthesis, high throughput screening data, -Omics data, and/or clinical data.
• Basic experience and/or practical understanding and interest in learning and applying modern deep learning techniques, including deep generative modeling, deep graph modeling, and foundation model development and transfer learning.
• Basic experience and/or practical understanding and interest in learning modern deep learning libraries including PyTorch; using version control with Git; 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.
• Independent thinking
• Experienced to work in interdisciplinary teams
• Excellent communication skills in English

Additional preferred skills

• Formal biological training or experience working with data derived from chronic-immune related diseases.
• Experience processing and analyzing single cell sequencing data.
• Experience working with traditional differential equation solvers or generative models for synthetic data generation.
• 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
• 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 utilizing AGILE methodologies.
• Access to a vast network in science and industry.
• 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, 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 team.
• Curriculum Vitae outlining scientific interests, research achievements, and a record of publications.
• 2 references will be asked for after submission as a part of the interview process.

The position is available as of October 1, 2023. Please submit your application to the attention of Dr. Douglas McCloskey before October 1, 2023, via our online Career Space.