Our mission as research center: Discover personalized medical solutions for environmentally triggered diseases to promote a healthier society in a rapidly changing world.

Models that learn relationships between biological interventions and patient outcomes can be conceived across experimental settings and contexts. One current goal is to generalize across diseases and experiments, through the development of platforms that enables reutilizing multimodal patient data as tailored, scalable models, capable of predicting patient states and transitions. In the context of an international consortium effort (Wellcome Leap - Delta Tissue), the Theis lab is looking for a postdoctoral researcher able to take lead in the developing extensions of previously developed computational (Palla et al. 2021) and modeling approaches (Lotfollahi et al. 2021), to work with generated and upcoming data obtained by our experimental collaborators. Datasets from the consortium are actively generated and will be focused on Triple Negative Breast Cancer (TNBC), Tuberculosis (TB), and glioblastoma multiforme (GBM).

Postdoc - spatial transcriptomics/single cell genomics/machine learning (f/m/x) 101330

Image Full time
Image Neuherberg near Munich
Image Postdocs

Your responsibilities

  • Implement module-based deliverables to analyze spatial transcriptomics data.
  • Explore self-supervised learning strategies to transfer spatial information to modalities of varying sparsity e.g. scRNA-seq, scATAC-seq.
  • Incorporate biologically-relevant prior information and use these to build interpretable models
  • Apply these models to cutting-edge multi-modal single cell measurements in consortia demonstration areas.
  • Active scientific reporting to consortia parties and collaborators. Goals and milestones of this project are tracked in quarterly reports, requiring active writing and presentation.

Your qualifications

  • PhD degree in Computer Science / Physics / Math / Computational Biology or related field
  • Knowledge and demonstrated experience with machine/deep learning methods
  • Strong programming skills in Python
  • Ability to handle multiple projects in a dynamic environment
  • Interest in discussing and exploring potential project ideas with collaboration partners

Desired qualifications:

  • Experience with spatial transcriptomics data and imaging
  • Demonstrated software development of scalable software projects in GitHub
  • Team management skills, to coordinate work with research assistants and co-leading

What we offer you

work-life balance
flexible working hours & working-time models
continuous education and training
30 days annual leave
on-site health management service
Image home office options
Image on-site nursery & holiday care
Image elder care
Image company pension scheme
Image discounted public transport ticket

Munich, with its numerous lakes and its vicinity to the Alps, is considered to be one of the cities with the best quality of life worldwide. With its first-class universities and world-leading research institutions it offers an intellectually stimulating environment.

Provided that the prerequisites are fulfilled, a salary level up to E 13 is possible. Social benefits are based on the collective agreement for the federal public service (TVöD). The position is (initially) limited to 2,5 years, under certain circumstances an extension can be arranged.

To promote diversity, we welcome applications from talented people regardless of gender, cultural background, nationality, ethnicity, sexual identity, physical abilities, religion and age. Qualified applicants with physical disabilities will be given preference.
If you have obtained a university degree abroad, we require further documents from you regarding the recognition of the degree. Please request the recognition as early as possible.

If you have further questions, simply contact Dr. Anna Sacher, +49 89 3187-2926, who will be happy to be of assistance.
Helmholtz Zentrum München
Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)
Institute of Computational Biology
Ingolstädter Landstraße 1

85764 Oberschleißheim

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