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be expected to develop, adapt and troubleshoot computational workflows as required by individual datasets and research questions. The position combines collaborative research with independent
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applicants are expected to engage in collaborative research with other members across the centre. As part of smaller, interdisciplinary teams within the centre, each selected candidate is expected to
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field of quantized reinforcement learning to be filled earliest by 1 November 2026 for a period of two years. About the Project: The project focuses on the theoretical grounding and algorithmic
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physics and experience with quantum many-body scars is an advantage. Experience within numerical methods for quantum many-body systems is required. Personal and collaborative skills are also important
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collaborative environment Takes ownership of scientific questions and actively advances projects Has strong communication skills and a track record of scientific dissemination Is enthusiastic about
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; Probability Theory and Analysis. The list may be updated with new areas up until the deadline for application. As a successful candidate you are expected to: * shine in individual and collaborative
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intelligence, starting 1 April 2027. You will design new sequence-to-expression deep learning models that predict gene expression from DNA sequence in plants, using new experimental datasets generated in the
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collaborative research with independent responsibility for genomic analyses, interpretation of results and development of research questions. You will collaborate closely with students, PhD students
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and should be prepared to work in a collaborative research team with the PI and project affiliates, including interdisciplinary research bridging social and natural science. The successful applicant
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, Denmark, invites applications for a two-year postdoctoral position in plant regulatory genomics and artificial intelligence, starting 1 April 2027. You will design new sequence-to-expression deep learning