Doctoral position (f/m/d) in Computational Biology and machine learning (E13/65 %)

Updated: 17 days ago

24.03.2021, Wissenschaftliches Personal

The Institute for Medical Microbiology, Immunology and Hygiene (MIH) at the Technical University of Munich is looking for a doctoral candidate (f/m/d) to join the group of Computational Biology. The position is initially available for three years and can be filled immediately. Our group uses data-driven mathematical modeling and machine learning methods to enable quantitative understanding of immune response and to inform pharmacological therapy (Pinto-Sietsma/Flossdorf et al. European Heart Journal – CVP 2020, Kretschmer/Flossdorf et al. Nature Communications 2020). Close collaboration with immunologists and clinicians and the integration of theoretical and experimental work is at the heart of our research.

Your tasks:

The successful candidate will work closely with Dr. Atefeh Kazeroonian to develop and employ novel machine learning and mathematical methods to address important biological questions with high clinical and immunological relevance. Special emphasis will be put on the integration of large datasets from various sources and types. Two main focus areas will be 1) Predicting antibiotic resistance in the context of Helicobacter pylori infection based on genomic and additional clinical data and 2) Investigating T cell differentiation and proliferation dynamics and detection of high-avidity T cell receptors. You will be using machine learning and mathematical methods to analyze various data types including single-cell RNA-seq, live-cell imaging, single-cell fate mapping and medical images. Close collaborations with the laboratories of Prof. Dr. Markus Gerhard and Dr. Veit Buchholz is an essential part of the PhD projects.

Your profile:

We are looking for highly motivated applicants with following qualifications:

o A solid background in mathematics, physics, computer science, computational biology or similar fields.
o Experience with machine learning methods would be a plus.
o Enthusiasm to learn new methods and techniques.
o Excellent programming skills in Python, R, and/or C/C++ and MATLAB.
o Ability to conduct interdisciplinary research in an international collaborative environment.
o Proficient written and spoken command of English.

We offer you:

We offer you exciting and challenging computational biology projects within a dynamic and collaborative research environment. Access to rich and high-quality experimental data based on state-of-the-art technologies is ensured through our close collaborations with different laboratories within the Institute of Medical Microbiology, Immunology and Hygiene (MIH). In addition, you will have the chance to interact with several other computational groups based in Munich.

Salary is paid according to remuneration group 13 TV-L (65%) of the pay scale for the German public sector. TUM is an equal opportunity employer. Therefore, women are especially encouraged to apply. Preference will be given to disabled candidates with essentially the same qualifications.

Applications:

Complete applications should be sent to Dr. Atefeh Kazeroonian (atefeh.kazeroonian@tum.de) and Prof. Dr. Markus Gerhard (markus.gerhard@tum.de). Please include a CV, a cover letter explaining why you are interested in the position and how you fit the profile, a brief summary of previous work experience and contact information of at least two referees.

Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.

Kontakt: Dr. Atefeh Kazeroonian, E-mail: atefeh.kazeroonian@tum.de


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