806 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions in United Kingdom
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of publications. Criteria Essential or desirable Stage(s) assessed at A PhD (or close to completion of a PhD) in Machine Learning or a similar area (e.g. in Computer Science, Electrical and Electronic Engineering
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and future directions within the field of human-computer interaction with a strong overview of how machine learning and/or probabilistic modelling/active inference can be integrated in it. A3 Evidenced
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Strong analytical skills and experience in developing and implementing machine learning/AI solutions using relevant languages and frameworks Excellent communication skills and proven ability to collaborate
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Desirable criteria Experience of advanced statistical and/or machine learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial
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population genetics, bioinformatics, computational biology, statistics or probabilistic machine learning and computer science. Experience of working with large genotyping or sequencing data sets A proven
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Research Fellow - OSMOSIS research programme (Internal candidates only) Apply online Job number SHMS00480 School / Service School of Health & Medical Sciences Department Nursing Location Myddelton
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modelling and computer simulation to study the earliest stages of embryogenesis in mammals. This full-time post in the group of Dr David Richards at the Living Systems Institute (http://projects.exeter.ac.uk
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the essential criteria for the post, which includes: Have or be about to obtain a PhD in computer science, engineering, mathematics or physical sciences area. Recent high quality research experience in
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Applications are invited for a behavioural science fellowship focused upon cross-cultural social psychology. The fellowship is jointly hosted by GCHQ (Classified Research Programme (CRP)) and the
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calculations. Conduct Accurate Calculations: Perform accurate wavefunction calculations on high-performance computer clusters to generate ab initio reference benchmarks. Collaborate and Publish: Work closely