We are looking for a joint

PhD candidate in Data Science

The Theis and Jäkel labs are looking for a highly motivated joint PhD candidate in Machine Learning in computational biology with high medical relevance, in particular for a project studying transcriptomic data obtained from patients with Alzheimer’s disease.

The Computational Health Center is globally recognized for innovations in data analysis and modelling of biological systems and diseases, anchored at Helmholtz Munich and the Technical University of Munich. The Institute for Stroke and Dementia Research is part of the Ludwig-Maximilians University Hospital and hosts internationally renowned scientists and is known for highly translational research from basic science to clinical studies.

At both our labs you will find a scientifically stimulating international environment with scientists from various disciplines. Together with renowned scientists and supported by an excellent infrastructure you will have the opportunity to make an important contribution for a healthier society at the interface between data science and medical research to become the outstanding data scientist of tomorrow.

Background: The Theis lab is researching Machine Learning methods in the context of computational biology, developing novel representation learning methods and applying them to model heterogeneities in single cell profiles e.g. from single cell transcriptomics to answer questions from basic biology to biomedicine. The Jäkel lab is researching oligodendrocyte pathology in neurological disorders, primarily in Alzheimer’s disease using transcriptomic approaches on human brain tissue in combination with stem cell-derived in vitro models.

Key responsibilities
  • Develop tools to analyze transcriptomic data obtained from postmortem human brain tissue (spatial Transcriptomics, snRNA-Seq)
  • Data integration from in vivo and in vitro data
  • Build upon our existing squidpy toolbox (Nature Methods 2022) and our graph-neural network approach NCEM (bioxiv) to determine single cell communication and what is changed during disease
  • Support experimental design based on initial disassociated and later spatial data sets
  • Masters degree in Computer Science / Physics / Mathematics or related field
  • Applied experience with machine/deep learning methods
  • Strong programming skills
  • Interest in medical/neuroscience background
  • Motivation to drive projects forward independently
  • Strong team spirit and willingness to work in international teams.
  • Interest in interdisciplinary work
  • Excellent English skills, written and spoken
Please send your electronic application (in English) in a single PDF file – including cover letter, statement of research interests, a description of a major accomplished scientific project (e.g. your Master thesis), CV, a complete list of publications, certificates and transcripts, and contact details of at least two references to: anna.sacher@helmholtz-muenchen.de