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Field
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CW and femtosecond optical spectroscopy methods. Preference will be given to candidates who already have some postdoctoral experience, but applications from recently graduated PhDs with an excellent
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are looking for: a highly motivated researcher with at least 3 years of research experience (possibly as part of the PhD) in a field related to mathematical analysis of partial differential equations (PDEs
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in the consortium. Your profile PhD in the field of mass spectrometry-based proteomics Ample experience in mass spectrometry-based proteomics, including sample preparation and hands-on use of modern
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of results in scientific journals Requirements: PhD in Physics, Engineering, Economics, Environmental Sciences, Mathematics, System Sciences or a related field training in formal, quantitative methods
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | 3 months ago
external funding (e.g., travel grants, PhD fellowships) We offer A securely funded position with an internationally competitive postdoctoral salary, outstanding employee benefits, and a family-friendly
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other actors conduct workshops with canteen cooks and farmers in collaboration with project partners Your qualifications: PhD degree in agricultural sciences, e.g. with a focus in agronomy, agro-ecology
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conferences Your qualifications: A Master’s degree (or equivalent) and a PhD in geophysics, physics, geosciences or a closely related field Experience in data assimilation and numerical simulations Knowledge
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or equivalent and a PhD (or close to completion) in computer science, math or comparable, or an applied/life science (e. g. engineering, biology, medicine) with a focus on data analysis and/or machine learning
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in the field of microbial ecology, molecular biology, microbiology or comparable with and a very good PhD Professional experience as a postdoc and experience in the supervision of qualification theses
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Qualifications / Experience: • A PhD in Physics, Geoscience or a related field • Proven expertise in numerical modelling using super computing clusters • Excellent knowledge of atmospheric physics • Proficiency in