Ludwig-Maximilians-Universität (LMU) München is recognized as one of Europe's premier academic and research institutions. The Gene Center is a central scientific institution of the LMU located in the heart of its Life Science Campus in Großhadern.
We are working towards improving our understanding of the regulatory landscape of cellular systems in health and disease across immunology, cancer biology, and evolution using high-dimensional molecular data (e.g. single cell and spatial transcriptomics, epigenomics). The analysis and integration of existing and new cutting-edge data sets, as well as the development of new computational tools to more efficiently and comprehensively leverage the ever-increasing wealth of data are a corner-stone of the lab’s efforts. Complementarily, we will be establishing and improving spatial-transcriptomics technologies towards the comprehensive spatio-molecular profiling of clinical samples and in vitro systems including organoids.
You will be working in an enthusiastic, multidisciplinary team comprising computational, wet-lab, and clinical scientists with an equal focus on scientific excellence and inter-personal competence. As one of the first members you would be able to play a primary role in the formation of the group scientifically and people-wise. You will have the opportunity to work on cutting-edge data-sets with ample room to contribute and strengthen your own scientific interests. As part of our group at the Gene Center of the LMU you will find excellent scientific working conditions including state-of-the-art computational resources with access to the LRZ as well as our own local high-performance cluster featuring CPU and GPU resources. The salary is determined by experience according to the German public sector pay scale TV-L.
The University of Munich is an equal opportunity employer. People with disabilities who are equally as qualified as other applicants will receive preferential treatment
- Master’s degree or equivalent qualification in computational biology, bioinformatics, data science, or a related field
- Practical experience in the analysis and interpretation of high-dimensional molecular data, in particular single-cell transcriptomics or closely related data types would be a plus
- Experience or strong interest in immunology, cancer biology, or spatio-molecular data (e.g. Slide-seq, Visium, MERFISH, CODEX)
- Ability to work independently and collaboratively with colleagues from different disciplines
- Proactive attitude and enthusiasm for research
- Fluent written and spoken English
Please send your application consisting of a cover letter and a curriculum vitae to firstname.lastname@example.org
Applications close 1 August 2021.