A position is open for a postdoctoral 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 integration of clinical microbiome and single-cell sequencing/proteomic data modalities to achieve clinical decision support in the molecular tumor board.
We are looking for you as of now, or upon agreement, as a
Postdoctoral Research Assistant (E13 TV-L, 100%)
The position will involve research in the interdisciplinary consortium comprising researchers at Universities of Tübingen, Heidelberg, Ulm and Freiburg, Germany. Research in this consortium builds on the recent success of personalized treatment of cancer patients in interdisciplinary tumor boards.
This position is part of a proof-of-concept study aiming at the investigation of two subsets of primary liver cancer specimen using latest sequencing and tissue purification techniques to identify intratumoral microbiome/-immune/proteome/exosome signatures as surrogates for targeted therapy of primary liver cancer. The latter will be combined with matched peripheral blood mononuclear cells (PBMC). Aim of this study is to translate a reduced, specific signature of this combined analysis into the molecular tumor board for treatment stratification of liver cancer patients. This study is carried out by researchers from above institutions with a strong collaborative track-record and with expertise in running the respective MTBs, liver cancer tissue analyses, sample preparation, different sequencing technologies and data analyses including translational machine learning (e.g. Pfister et al., Nature 2021).
The candidate will apply and develop machine learning approaches to identify therapy response associated identify intratumoral microbiome/-immune/proteome/exosome signatures. Upon validation in independent patient cohorts, this information will then be used to stratify patients prior to therapy to maximize the therapeutic impact and to minimize adverse effects as well as to provide new personalized therapeutic targets for therapeutic intervention.
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.