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The Faculty of Science invites applications for a POSTDOCTORAL RESEARCHER IN MACHINE LEARNING FOR NATURE CONSERVATION starting from August 2025 or as agreed. The Postdoctoral Researcher will be
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Validation of Integrated Approaches (FHAIVE ). The researcher will focus on applying machine learning (ML) techniques to knowledge graphs (KGs) for advancing projects in chemical safety, toxicology, and drug
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. We require the candidate to have documented experience in either large-scale genomics data analysis with computational or approaches/biostatistics, or machine learning/deep learning. Experience with
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research / molecular biology. The proposed project is intended for an MSc-level person who wishes to acquire PhD degree. PhD Trainees in my laboratory typically graduate within 3-4 years with competitive
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focus of the position is on application and advancement of modern artificial intelligence (AI) methods in drug discovery and development. An ideal candidate will have strong background in machine learning
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advancement of modern artificial intelligence (AI) methods in drug discovery and development. An ideal candidate will have strong background in machine learning, computational chemistry, or related fields, with
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talented and highly motivated Doctoral Researcher in Quantum Computing In this position you will carry out research in quantum machine learning and quantum information science. Your research will focus
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of large-scale genomic data sets is a requirement for this position. Experience with data integration, machine learning, network science, cancer biology, and/or gene regulation is considered an advantage
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research on emotion AI, learning processes and perception engineering for AI-based solutions e.g. in education and nursing. HI research combines the strengths of both humans and machines, emphasizing mutual
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dysfunction. An ensemble of multi-scale computational approaches (molecular dynamics simulations, quantum chemistry, machine learning) are applied to study the mechanistic aspects of biomolecules in great depth