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%, limited for 3 years, start: as soon as possible) in the trilateral program “Future Proofing Plants to a Changing Climate” (funded by DFG, UKRI-BBSRC, NSF, USDA-NIFA) Who we are: The research group Symbiosis
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%, limited for 3 years, start: as soon as possible) in the trilateral program “Future Proofing Plants to a Changing Climate” (funded by DFG, UKRI-BBSRC, NSF, USDA-NIFA) Who we are: The research group Symbiosis
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optimization or discrete algorithms. Profound mathematical modeling and programming skills. Experience with the design and analysis of graph algorithms or multiobjective optimization models is a plus. Very good
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skills, including in intercultural contexts Very good English skills Note: Prior experience with eye tracking or literature in the field of crowd psychology is not required. Instead, we value scientific
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of seismic methods and numerical simulations, Good PC and programming skills (e.g., with Python, MATLAB), Experience with measurement techniques and field measurements using sensor technology (ideally using
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environment Immunity status Please note that employment is contingent upon proof of immunization or immunity against the measles virus, in accordance with applicable legal and medical requirements
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, Computational Biology, Systems Biology, or a related field Strong programming skills in R and/or Python Experience with single-cell or multi-omics data analysis Interest in cancer biology, particularly leukemia
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tools (e.g., Python programming) is an advantage. You enjoy working in an international team and have good communication skills. Proficiency in spoken and written English is required. For more information
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participation in the related Graduate School training programs. Qualifications The applicants should possess: an excellent or very-good university degree in economics, business studies, agricultural sciences with
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literacy and basic programming skills (R, Python), or the willingness to develop these skills Analytical mindset, with a keen interest in advancing proteomic methodologies We offer Cutting-edge proteomic