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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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chronometabolic research Analysis and quantification of circadian rhythms by rhythm analysis software (Cosinor, JTC cycle, R etc.) Rhythm analysis in human 24-hour time series data and omics data Writing
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ecology, macroecology, metacommunities, and/or analysis of ecological time series. The applicant should have a strong track record of scientific publications. Over the past years, we have compiled one
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for real-world applications in agriculture, animal welfare, and environmental research. Analyze and model diverse data types, including image, time-series, and tabular data. Develop and apply methods
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The Leibniz Institute for Financial Research SAFE - Sustainable Architecture for Finance in Europe - (www.safe-frankfurt.de ) promotes scientific research, transfer work to the public and
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Nanopore sequencing (RNA, cDNA, or DNA). Familiarity with machine learning, particularly in biological data contexts. Skills in signal processing, particularly time-series or nanopore signal data. Experience
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and the Biogeochemical Modelling Research Group in the department of Physical Oceanography at IOW, you will curate a time series of in situ, remotely sensed and modelled inherent and apparent optical
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financial supplement for a German job ticket (Deutschland-Ticket) at both locations. For further information, please contact Dr. Marcus Seidel at +49 40 8998‑6034 (marcus.seidel@desy.de ). Please submit your
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(Heidelberg University), Holger Bettinger (University Tübingen) and Michael Gottfried (University of Marburg), financially supported by an ERC Synergy Grant starting in April 2023. The aim is to synthesize