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Field
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areas is expected: numerical analysis, scientific computing, model reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming
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projects of the research group Qualification Required: A diploma and a PhD in microbial natural product chemistry Hands-on experience and a strong understanding of metabolomics/dereplication of natural
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Max Planck Institute for Biology Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 14 hours ago
once a year to meet with the consortium. The position is for two years, with the possibility for extension. Requirements PhD (or equivalent international degree) or enrolled in a PhD degree program (or
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
the current management concept adequately address the emerging challenges posed by climate change and a fast-growing fishery? How can the management concept be improved, potentially by learning from management
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collaboration with our clinical colleagues for investigating visual motion in a group of healthy subjects. The successful applicant holds a PhD degree (or equivalent) in a relevant academic area such as applied
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, behavioral, experimental and/or applied microeconomics or other related fields, and you have completed your PhD by job start or are close to completing it. You have already proven your relevant knowledge and
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interpretation of OMICs datasets (DNA, RNA, proteome) Supervision and technical guidance of Bachelor’s, Master’s, and PhD students, as well as technical staff within the project context Participation in teaching
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preclinical in vitro and in vivo models Supervise and mentor MSc/MD/PhD students Collaborate with national and international research partners Present your results at scientific meetings Publish your findings
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change #utilize a participatory system dynamics modeling to match resilience patterns with best-fit learning cases from various regional contexts in Europe #develop a resilience performance framework for