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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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Master’s degree (or equivalent) in a relevant discipline such as computer science, mathematics, physics, or data science. They should have strong analytical skills related to statistics, machine learning
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. Requirements: university degree (master or diploma) in chemistry or physics and profound knowledge in computational and theoretical physics/chemistry A sound knowledge of simulation methods and actinide
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) and the German Academic Exchange Service (DAAD) since 2007. Under this CAS-DAAD joint programme up and coming young Chinese scientists from the University of Chinese Academy of Sciences (UCAS) and CAS
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the Federal Ministry of Research, Technology, and Space (BMFTR). It includes an interdisciplinary training program based on the concept of a graduate school. In the 2nd year there is the option of increasing
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%, Service Location: Clausthal-Zellerfeld) The research group Dependable and Autonomous Cyber-physical Systems (DACS) at the Institute for Software and Systems Engineering (ISSE), Clausthal University
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of Photogrammetry and Remote Sensing and together with other chairs being part of the RTG. Requirements: good or very good university degree in computer science, mechatronics, robotics, electrical engineering, or a
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with a possibility of extension. Research Focus IMPRS-GS: Projects span experimental (genomics, transcriptomics, proteomics, etc.) and theoretical (bioinformatics, computational biology, etc
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will be matched with PIs’ projects. Who can apply? We are looking for excellent candidates with a completed Master’s degree in various fields (Life Sciences, Bioinformatics, Mathematics, Physics
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project work plan and milestones Your profile Completed university studies (Master/Diploma) in the field of Chemical/Metallurgical/(Mineral) Process Engineering, Data Science, Statistics, Machine Learning