288 programming-"the"-"DAAD"-"IMPRS-ML"-"CNRS-ENS-UCBL" Postdoctoral positions in United Kingdom
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models and/or climate
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Requirements: A completed doctoral degree in chemistry, bio technology or a related field. Strong programming skills in Python, R, or similar languages. A track record of research competence and initiative
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Banking. Your skills and attributes for success: Expertise in one or more of the following areas: Machine Learning, Reinforcement Learning, or LLM orchestration. Strong programming skills in Python and
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scientific programming and independently managing a discrete area of a research project are desirable, but not essential. The deadline for applications is midday on September 11 2025. Interviews will be
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specialist knowledge in mechatronics design and control, and proven programming experience in Python, MATLAB or C/C++. Informal enquiries may be addressed to Professor Liang He (email: liang.he@eng.ox.ac.uk
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or innovative solutions. To liaise with research colleagues and make internal and external contacts to develop knowledge and understanding to form relationships for future research collaboration. To plan and
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interdisciplinary research programme involves national and international collaborators. We are a vibrant, enthusiastic, innovative and strategic enterprise with an internationally leading position to make a real
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Programming experience in MATLAB or Python for data analysis Hands-on experience building and optimizing test setups for photonic devices We are looking for someone who is passionate about photonic technologies
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. Proficiency in the use of statistical programming languages and analysis of large datasets and strong publication records would be essential. Previous experience in atmospheric dynamics and predictability is