2y Postdoc position at the University of Tübingen available Join us for a project at the intersection of machine learning, population genetics, and medical research in southern Germany. The genetics of human populations are entangled through shared ancestry, which introduces correlations in medical and genome wide association studies. This project aims to enhance the accuracy of medical studies by leveraging large-scale genealogical analysis. Therefore we will infer huge ancestral recombination graphs that describe the local ancestry of the individuals as a sequence of thousands of genealogical trees along their genomes. We will develop machine learning techniques to process these graphs and classify individuals based on the inferred genetic relationships and disease states within cohorts. By integrating fine-scale genealogical analysis with medical research, we aim to improve cohort selection and the robustness of medical study outcomes. ---- The AI & Data Science Fellowship Program, a cooperation between the University of Tübingen, distinguished as excellent by the Federal Government of Germany, and Boehringer Ingelheim, a leading pharmaceutical company, is inviting applications for a Postdoctoral Research Fellow – AI & Data Science (f/m/d; E13 TV‑L, 100%) to work on cutting-edge and exciting AI & data science research topics that generate real added value for human and animal healthcare. The initial fixed-term contract will start as soon as possible and have a duration of 2 years with possible extension. About the project In this project, you will     infer ancestral recombination graphs from large-scale human biobank data;     identify patterns in genomic data associated with immune diseases;     develop Graph Convolution Networks to analyze large ancestral recombination graphs;     apply the developed tools to real-world data to support medical research. Your host: Computational Population Genetics Group led by Dr. Franz Baumdicker. Your collaborating scientist: Zhihao Ding (Head of Global Human Genetics and Animal Health Genomics) at Boehringer Ingelheim. Your profile The ideal candidate will bring     a Ph.D. or equivalent in Computational Population Genetics, Machine Learning, Bioinformatics, Medical Informatics, Computer Science, Mathematics, or a related discipline. This position is also suited for researchers who have recently finished or are about to finish their PhD.     demonstrated experience in human population genetics on real and simulated data     experience in translating methodological advances into practical applications     experience in phylogenetics, coalescent theory     experience in graph convolution networks     proficiency in coding (Python)     a competitive track record of scientific publications     a keen interest in interdisciplinary work     the ability to work both independently and as part of a collaborative team Our offer This position offers you     exciting research at Europe’s leading AI campus     cooperation with a research-driven global pharmaceutical company     collegial and supportive work atmosphere     remuneration in accordance with the TV‑L (collective agreement for public employees of the German federal states) as well as all corresponding benefits     30 days/year of paid vacation     potential for travel to conferences and professional development workshops     career mentoring     opportunity to gain leadership experience by supervising research assistants     extensive visa and onboarding assistance     discounted public transportation, etc. We value diversity in science, and particularly look forward to receiving applications from women, non-binary people, and researchers from underrepresented groups across cultures, genders, ethnicities, and lifestyles. We actively promote the compatibility of science, work, studies, family life and care work. In case of equal qualification and experience, physically challenged applicants are given preference. Further information For further information on the project, please reach out to franz.baumdicker@uni-tuebingen.de How to apply Please send your application (including a motivation letter, CV, certificates, bullet point list of representative publications and their relevance for this project, contact details of 2 academic references) with the subject “AI and Data Science Fellowship Program Application” via e‑mail to franz.baumdicker@uni-tuebingen.de Application deadline: 30.11.2024. Franz Baumdicker (to subscribe/unsubscribe the EvolDir send mail to golding@mcmaster.ca)