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on probability, partial differential equations, large deviations, stochastic analysis, optimisation and machine learning. The successful candidate will contribute to the activities of the Machine Learning & Data
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Neurodevelopment. You will develop, implement, and apply computational pipelines to analyse large-scale genomic datasets generated through Perturb-seq and other functional genomics approaches. You will use state
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University of California, Los Angeles | Los Angeles, California | United States | about 11 hours ago
clinical data. A major focus of the position will be identifying genomic and immunologic features associated with variation in immune responses and clinically relevant phenotypes. A Ph.D. or equivalent
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visualizing large-scale, complex data. For the vacant position, we particularly search for a colleague experienced in computational text and/or image analysis and processing platform data. Your future tasks
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how clinical blood tests are used. The chosen candidate will develop novel theory, large-scale data pipelines, and collaborate with clinicians to drive impact from these models, and use them to benefit
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collection, and statistical analysis. Proficiency in statistical software (e.g., R, SAS, STATA) and data management techniques. Demonstrated experience in analyzing large epidemiological datasets. Excellent
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, Python or R Experience in manipulating and analyzing large observation data or model outputs Working knowledge of terrestrial biogeochemistry and nutrient-cycling processes Strong communication skills
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(Large Language Models, Convolutional Neural Networks, Machine Learning) for analysis and classification of data.
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analyses within this large-scale field experiment, working closely with an international consortium of health economists, clinicians and implementation scientists. Join us to help generate the evidence
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interiors. This work will rely on large-scale atomistic simulations paired with machine-learning interatomic potentials. Duties: ● The postdoc will generate density functional theory reference data, use