7 coding-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"FEMTO-ST" positions at Imperial College London
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maths, science, coding), and (3) world modelling for multimodal planning and simulation. Adaptive FMs thus open a path towards more efficient and more capable generative AI. Within the project, you will
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, failure modelling of fibre-reinforced composites using FEM, use of Artificial Intelligence for surrogate models An interest or experience with structural optimisation Experience in scientific coding (e.g
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inside the London Secure Data Environment, working with linked primary and secondary care records for an unselected London-wide population. That means curating coded clinical, prescribing and pathology
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etc. We expect excellent skills in mathematics, especially knowledge in formal methods, stochastic systems and processes, the foundations of deep learning. Experience coding with deep learning libraries
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for biological data interrogation and interpretation. Experience of using R and/or python code for bioinformatics data analysis of multiplex complex datasets. This post will provide the opportunity to develop and
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validation and evaluation of transportability across datasets and population subgroups. Clinical questions will be translated into robust data pipelines and reproducible analytical code incorporating version
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to changing demands. Have proven ability to comply with regulations and codes of practice. The chance to join a supportive and friendly team that welcomes innovation and works collaboratively with multiple