53 machine-learning-phd-in-denmark Postdoctoral positions at Nature Careers in Germany
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg (including ELLIS Life Heidelberg and the AI Health Innovation Cluster ). Your
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, particularly in C++ and Python Good communication skills in spoken and written EnglishInterest or prior experience in machine learning techniques is considered an asset. You may expect a multifaceted and
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cutting-edge big/deep data analysis methods, including machine learning and artificial intelligence. The ideal candidate will therefore have a strong background in data science and in the application and
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Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological
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phage application strategies and contribute to publications and conference presentations Engage actively in team meetings and the interdisciplinary PHAGE-PRO network Your profile PhD in life sciences
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of reports, publication of results Your qualifications: Completed university studies (M.Sc./ M.Eng.) and PhD in polymer science or a comparable field of study Relevant experience in thermal analysis and fire
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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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of machine learning and health sciences, with unique access to experimental and clinical data. Embedded in Munich’s thriving AI landscape, fellows benefit from world-class facilities, interdisciplinary
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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
apply machine learning/AI methods for ecological analyses Expedition experience Further Information The AWI is characterized by The AWI is characterized by our scientific success - excellent research