Doctoral Research Assistant (m/f/d, E13 TV-L, 65%)

A position is open for a doctoral research assistant in the Clinical Bioinformatics group at the University Hospital/University of Tübingen. The available position focuses on development and application of machine learning approaches for the simulation based reconstruction of differentiation processes of immune cells during viral infections.

We are looking for you as of now, or upon agreement, as a

Doctoral Research Assistant (m/f/d, E13 TV-L, 65%)

The position will involve research in the interdisciplinary consortium comprising researchers at Universities of Tübingen and ETH Zurich. Research in this consortium builds on its recent work on T cell exhaustion in chronic infection (Sandu et al. 2020, Cerletti et al. 2020, Gupta et al. 2020).

This position is part of an initiative investigating T cell exhaustion, an immune cell state associated with persistent viral infections as well as with impaired host immune defense in cancer affecting more than 2 billion people worldwide. The causal molecular mechanisms leading to exhaustion remain elusive due to the difficulty to account for the complex and dynamic interplay of regulators of T cell differentiation in vivo. We aim at identifying novel causal transcriptional mechanisms with an integrated multiplexed, in vivo, single-cell intervention screen and causal inference approach. We will perform a multiplexed single-cell CROP-seq intervention screen in conjunction with time series single cell RNA seq readout of antigen specific CD8+ T cells in the course of chronic infection. We propose deriving causal Markov models from the resulting data by comparative and integrative RNA velocity analysis building on our recent simulation based trajectory inference approach (Gupta et al. 2020). The method development and application to this end constitutes the core goal for the advertised position.

This approach will generate testable hypotheses on specific driver genes deciding on the fate of CD8+ T cells. In conjunction with our international partners we will validation the fate determining potential of these genes will be performed in vivo by selective targeting in LCMV-specific CD8+ T cells. Validated mechanisms and driver genes in our in vivo model system will motivate rational interventions to beneficially interfere with T cell exhaustion in the context of human chronic infections or cancer.T

The ideal candidate brings along a degree that demonstrates an interdisciplinary background in both life and formal sciences. While a background cancer-/immune biology and single cell proteomic experiments are a plus, a solid background in mathematics, statistics and programming is required to carry out the planned algorithm developments and data analysis. A fluent level of English is mandatory. We are looking for a highly motivated candidate with excellent communication skills that is capable of working in an interdisciplinary environment and can team up with scientists for experimental as well as computational analysis. The candidate should have a high degree of initiative. We offer work in a highly stimulating environment with state-of-the-art infrastructure, providing the successful applicant with unique opportunities to develop a strong interdisciplinary portfolio in both experimental and computational biology.

The University aims to increase the proportion of women in research and teaching and therefore urges suitably qualified women scientists to apply. Qualified international researchers are expressly invited to apply. Disabled persons with equal aptitude will be given preferential consideration.

Applications with a motivation letter, full CV, diploma(s) and two contacts for further references should be sent online to Prof. Dr. Manfred Claassen.