337 computer-programmer-"Prof"-"Embry-Riddle-Aeronautical-University"-"Prof" Postdoctoral positions in United Kingdom
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
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projects. The role holder will be expected to plan and manage their own research and administration, with guidance if required. They must be able to communicate material of a technical nature and be able
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situ/operando experiments and associated cell design is desirable. Familiarity with one or more of the following techniques is highly desirable: X-ray and neutron diffraction, computational chemistry
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situ/operando experiments and associated cell design is desirable. Familiarity with one or more of the following techniques is highly desirable: X-ray and neutron diffraction, computational chemistry
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engineering, computer science or other field relevant to the proposed area of research. You should have a good track record of robotic publications/presentations in the field of healthcare, possess sufficient
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, operations research, computer science, mathematical finance, or a related field, the successful candidate will demonstrate the ability to develop independent research ideas and contribute to advancing our
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, operations research, computer science, mathematical finance, or a related field, the successful candidate will demonstrate the ability to develop independent research ideas and contribute to advancing our
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to understand immune microenvironmental interactions; Integration and interpretation of complex datasets in collaboration with computational scientists You will be expected to take a lead in experimental design
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based on the understanding that early experience shapes the way our brain is constructed. While the “ground plan” of the brain is genetically determined, it is also influenced by environmental experience
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related to gravitational wave astronomy. The primary aim will be the development of advanced approaches for computational Bayesian Inference to measure the properties of Compact Binary Coalescence signals