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theoretical and/or computational research in Nonequilibrium Statistical Physics and Active Matter, under the supervision of Ramin Golestanian. For more information concerning our current areas of research
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will engage in theoretical and/or computational research in Nonequilibrium Statistical Physics and Active Matter, under the supervision of Ramin Golestanian. For more information concerning our current
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regulation, RNA biology, protein biochemistry, stem cells, bioinformatics, sequence analysis, mathematics, statistics, molecular evolution, or biophysics, and wish to work at the Max Planck Institute
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experience in the use of mass spectrometry • Good working knowledge in the application of statistical analysis procedures • Sound knowledge of ecological and evolutionary concepts • Basic knowledge in the use
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)physics, chemistry, or a related field. A solid knowledge of the theory of molecular systems and statistical mechanics, as well as skills in molecular dynamics simulations, is highly desirable. Proficiency
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modeling and computational workflows Knowledge about machine learning: statistics and deep learning Experience in data analysis, visualization and presentation Good programming skills in languages such as
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scientific questions Proficient use of scientific software (e.g., Gatan DigitalMicrograph, Python, Origin, Matlab) Basic knowledge of scientific data analysis and statistical evaluation Good knowledge of MS
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the application of molecular biological methods experience in the statistical analysis of research results or willingness to acquire such experience very good knowledge of MS Office, including Word, Excel and
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scientific questions Proficient in scientific software (e.g., Gatan DigitalMicrograph, Python, Origin, Matlab, SRIM/TRIM) Basic knowledge of scientific data analysis and statistical evaluation Good command
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of Econometrics and Statistics, esp. in the Transport Sector and co-supervised by Prof. Dr. Klaus Bogenberger, Chair of Traffic Engineering and Control, TU Munich. Requirements: Excellent, very good or good