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Field
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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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, offering the best possible means for networking with colleagues and pursuing sports alongside work Opportunity to develop your strengths, e.g. through a comprehensive training programme; a structured
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the courses Advanced Mathematics 1–2 and/or Statistics at the TUM Campus Straubing. Your profile: Above average master’s degree in mathematics or (theoretical) computer science with a focus on discrete
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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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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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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
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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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English Languages Courses are usually held in English. The dissertation is written in English. Mode of study Less than 50% online Programme duration 6 semesters Beginning Only for doctoral programmes: any
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computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
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accepted. Providing GRE General Test scores is highly recommended but not mandatory. In addition, please note that the minimum scores for the GRE General Test (for admittance to the programme) vary based