106 phd-computational-"IMPRS-ML"-"IMPRS-ML"-"IMPRS-ML" positions at Imperial College London in United Kingdom
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to assimilate in-house expertise but also to gain further experience through collaborative work (on theory, computational chemistry, other spectroscopies, etc) elsewhere in Imperial, the UK, and abroad. The
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, the Department and the College To provide guidance to PhD Students Contribute to bids for research grants To conduct and plan own scientific work with appropriate supervision. To maintain highly organised and
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range of mouse models, live imaging of primary cells and matrisome analyses. You will actively participate in the research programme of the Lloyd Group. You will conduct and plan your own scientific work
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. The research programme will be conducted in the Blackett Laboratory at Imperial College, with work also taking place at the experimental sites in Japan, the USA and Geneva as well as collaborating institutes
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will be expected to participate in co-supervision of project students, oversee smooth and safe operation of the lab. Applicants should hold a PhD in synthetic organic chemistry or physical organic
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the Molecular Science Research Hub building in west London. You will work alongside a dynamic team of researchers that span synthetic chemistry and computational modelling. Catalytic hydrogenation processes
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part of a multidisciplinary team comprising spectroscopists, bioinorganic chemists, synthetic and computational chemists to tackle how CO2 fixation occurs through a biomimetic approach? Then this role
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problem-solving skills and deep expertise in the development of complex computational models. Candidates who have not yet acquired their PhD would be appointed at the Research Assistant level. The
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, applying and validating your algorithms through laboratory experiments. A PhD in Chemistry, Biology, Computer Science, or related fields with a focus on protein engineering. Proficiency in Python programming
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Contribute to the supervision of junior researchers and students as opportunities arise A PhD in a relevant quantitative discipline (e.g. mathematical modelling, geo-statistics, machine-learning) Experience