THE CHARITÉ – UNIVERSITÄTSMEDIZIN BERLIN
is a joint medical faculty, which serves both Freie Universität Berlin and Humboldt Universität zu Berlin. As one of the largest university hospitals in Europe with an important history, it plays a leading role in research, teaching and clinical care. The Charité university hospital has also made a name for itself as a modern business with certifications in the medical, clinical and management fields.
Postdoctoral Position – Scientist (m/w/d)
CC02, Institute for Biochemistry, Group Biochemistry and Systems Biology of Metabolism
Charité Campus Mitte
Computational Biology: Machine learning to predict metabolism and to dissect a huge cellular connectivity network.
We are looking for an enthusiastic postdoctoral scientist (Computational or network biology) to join Prof. Markus Ralser’s laboratory at the Charité – Universitätsmedizin Berlin, Institute for Biochemistry. The Ralser laboratory is renowned for its studies that understanding how cellular metabolism, the network of biochemical reactions in the cell, is regulated, how it evolved, and how it maintains functional integrity in the ever-changing environment the cell is exposed to. This research addresses fundamental problems in the life sciences, where knowledge about cellular metabolic systems is required to develop new therapeutics and to understand the molecular basis of disease.
Your area of responsibility:
When cells are challenged or change growth conditions, major changes in gene expression emerge. Typically, hundreds to thousands of genes respond. But, the individual genes do not respond in isolation to each other; there are many co-dependencies between the genes that respond. These connections emerge from gene function, regulation, and gene expression noise. Hence, despite cells have thousands of genes, they have not thousands of fully different response mechanisms.
This project is to learn to predict the response of a cell from measuring a subset of its proteome, and in this way, reconstruct the connectivity network that exists between the genes. We are currently generating a large multi-omic network, in which the metabolic phenotype of a yeast cell will be linked to all of its genes. We have created a library of ~5,000 yeast gene deletions strains with a functional metabolism, have recorded metabolomes for all of them, and are in the process of completing proteomes and an ionome for them. We can hence link every gene in the genome to its impact to proteome, metabolome and phenome. This resource is one of the largest and perhaps the most complete, multi-omic dataset available for any species, and enables to dissect the interconnectivity network of gene regulation. The project will pave the way to develop functionally predictors out of human omic data, for instance, genomes or proteomes, for disease progression.
We are hence looking for a computational biologist with a background in machine learning and biological networks, eager to work with the perhaps largest multi-omic dataset available, to predict the response of an entire cell, when conditions change.
- PhD or Research Doctorate, in the basic sciences;
- Productivity documented in published research articles or patents;
- Experience in the handling of large datasets, and respective programming and statistical skills
- Background in machine learning and/or network biology
Lenght of employment:
36 Months (with the possibility for extension and tenure)
Pay (pay scale):
Acc. to collective agreement TVöD VKA-K
Employees are grouped into pay scales according to their qualifications and personal requirements. You can find our collective bargaining agreements (Tarifverträge) here: https://www.charite.de/en/careers/
For further information please contact Prof. Markus Ralser, email@example.com, +49 (0)30 450 528141
Please send your application quoting the reference number by 09.09.2019 to:
Charité – Universitätsmedizin Berlin
CharitéCentrum 2 – Grundlagenmedizin, Institut für Biochemie
Mr. Prof. Markus Ralser
Charitéplatz 1, 10117 Berlin
DIE CHARITÉ – UNIVERSITÄTSMEDIZIN BERLIN
makes its human resources decisions based on suitability, competence and professional performance. At the same time, it strives to increase the percentage of women in management positions and takes this into consideration where candidates are equally qualified within the limits of what is legally possible. Applications from people with a migrant background are also explicitly welcome. Severely disabled applicants are given preferential consideration in the case of candidates with equal qualifications. An extended certificate of conduct must be submitted. Any travel expenses incurred cannot be reimbursed.
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