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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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research on the effects of different forest management regimes on the protective function of forest ecosystems. The work is embedded in a collaborative project coordinated at the Technical University
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interdisciplinary collaborations such as the Collaborative Research Center 1371 “Microbial Signatures – Functional Relevance in the Digestive Tract” (https://www.sfb1371.tum.de/) and access to different core
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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning
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experiences in working with remote sensing data, climate data and programming skills (R or Python) are desired. You enjoy working in an international team and you are keen on developing a key set of research
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spectrometry (GC-MS), electro-antennographic detection (EAD), RNAi knockdowns, and behavioral olfactometer assays—to elucidate how divergence in CHC perception has potentially contributed to prezygotic
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(https://soilsystems.net/ ), a Priority Programme (SPP 2322) funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation). Within SoilSystems, scientists from different disciplines from
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Science, Transportation Research Part B, or conferences such as SIGKDD, ITSC, CIKM) Strong programming skills in Python Strong interest in scientific research with the goal of obtaining a doctoral degree
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platform for early detection of cardio-metabolic diseases as well as characterization and classification of skin diseases. You will be part of our highly impactful research programs funded by European and
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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