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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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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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within the Institute of Theoretical Computer Science at TU Dresden. The main research area is the design and analysis of algorithms and data structures, with possible focus areas including randomized
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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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agreement of the federal states). The successful candidate will carry out research tasks related to the structural and biochemical analysis of protein-nucleic acid complexes relevant in gene-regulation
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perform a risk analysis of the resulting model outputs Present your scientific results at conferences, workshops, and seminars, and publish the work in peer‑reviewed journals Collaborate with project
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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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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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disposal subject to pending project approval. The long-term safety of a deep geological repository of high-level radioactive waste requires a detailed understanding of the interactions of radionuclides and
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hierarchically organised samples. To achieve this, we need to improve our understanding of the physical image formation and data recovery processes, among other topics. The advertised positions will focus