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Field
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the risks. You will have: a PhD in one of the relevant STEM disciplines, such as mathematics, statistics, computer sciences, theoretical food, ecological or physical sciences, etc. skills in mathematical
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computer codes to solve some of the daily research problems and have experience with high performance computing. You should have a PhD in Chemistry, Physics or Materials Science with a proven research track
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Application Deadline 23 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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highlights the urgent need for novel approaches. Antimicrobial peptides (AMPs) are an emergent technology platform which are cost-effective to manufacture and have potential to control wound infection. Despite
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associate with expertise in data science to join the King’s BHF Centre of Research Excellence and contribute to a growing cardio-immunology research programme. Inflammation is increasingly recognised as a key
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computational workflows on a high-performance cluster. You will test hypotheses using data from multiple sources, refining your approach as needed. The role also involves close collaboration with colleagues
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conventional boundaries and pursue hypothesis-led science. We will make every effort to support the successful candidate to research independence through the programme, and with training and mentoring
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: PhD or equivalent degree in Robotics, Computer Science, Machine Learning, AI, Control Engineering, or a related field. Excellent programming skills and experience with related tools and software. A
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. Qualification requirements The selected candidate should have a master’s degree in a related field: e.g., civil engineering , mechanical engineering , computational materials science , or applied mathematics
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying