132 parallel-computing-numerical-methods-"Simons-Foundation" positions at King's College London
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: Biostatistics & Health Informatics. Contact details:Ben Carter (Professor of Medical Statistics). ben.carter@kcl.ac.uk Location: Denmark Hill Campus. Category: Research. About us: The Department of
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2000 staff and holds an Athena SWAN Silver award. It has a comprehensive programme of initiatives to support an inclusive environment and culture, and to promote diversity across our staff and student
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for molecular simulations Track record of method development for molecular simulations Experience of working effectively in a team Experience of working with high-performance computing * Please note that this is
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PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods to analyse datasets Experience in statistical or scientific programming (ideally R and/or
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successful team. About the role: Develop a complete familiarity with the operation and recovery of all business-critical systems within the buildings Carry out the planned preventative maintenance programme
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both individual and collective wellbeing. Employee support at King’s includes flexible working arrangements, paid maternity/shared parental leave, menopausal support, an active wellbeing programme
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methods for generating simulation models of healthcare pathways in Python. The Health Service Modelling Associates (HSMA) Programme is an online national training scheme for public sector analysts
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’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across five Departments. The Department of Women and Children’s Health is a lively and supportive
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. Highly responsive with excellent organisational and time management skills to prioritise effectively and meet tight deadlines. 3. Excellent numerical and data management skills with the ability
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, administration or projects 2. Highly responsive with excellent organisational and time management skills to prioritise effectively and meet tight deadlines. 3. Excellent numerical and data management