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committed work style Advanced experience in preparing data according to conversation-analytic criteria and standards (e.g., transcription, metadata documentation) and relevant tools (FOLKER, ELAN, etc
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methods and ideas PhD in Physics, meteorology or a related subject Experience with running and evaluating models English skills that allow one to communicate in an international working environment, and to
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coding experience with e.g. Python/Matlab/R Practical experience with High Performance Computing, and scientific programming and a willingness to learn to work with high-performing computing systems
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 23 days ago
description Single molecule X-ray scattering experiments with free electron lasers offer a new route to the structure determination of biomolecules. Due to the super-low signal-to-noise-ratio, computing
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groups in theoretical and experimental particle physics and astrophysics. The successful candidate will conduct research on precision calculations for high-energy collider experiments and Monte Carlo
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, you must have a PhD in a relevant field. As a suitable candidate, you have expertise in deep convective cloud processes and experience with scientific data analysis. Prior experience in applying machine
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
additional advisors from institutions outside of HIFMB. HIFMB continues to strive for transformation and to bridge the science-policy interface. Therefore, experience or interest in transfer activities is a
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of programming languages such as Python is an advantage. Practical lab skills and enjoying experimental work is also a plus. Involvement in teaching (supervising practicals or tutorials) is possible. Your tasks
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experience through articles in internationally recognized refereed journals or working papers suitable for publication. You contribute in-depth knowledge of methods of applied microeconomics, experimental
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to develop an autonomous platform for organoid culturing and analysis to address key challenges in organoid-based experiments. This interdisciplinary project will leverage robotic systems for high-throughput