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Field
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bring expertise in computational methods (such as machine learning, chemo-informatics, molecular dynamics simulation, structural biology) and / or experimental methods (such as biophysical analysis
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instrumentation and analysis, data management, software applications, record keeping, compliance training, and the principles of scientific study design. Learning both general and specialized research skills
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tissue specimens Assemble analysis pipelines using machine learning to process tissue data reproducibly and at scale Conduct analyses using programming languages such as R and Python Collaborate with other
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Requirements: Applicants must be enrolled in a Master’s Degree in Computer Engineering or related fields. Proof of enrolment must be provided by the time of contracting. However, candidates may initially submit
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/knowledge graphs, and carbon accounting. The Research Fellow will help develop and lead the CognitionX Lab (https://cognitionx-lab.github.io/ ) with Dr. Jinying Xu, Assistant Professor and Director of
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viability data to discover new biomarkers and treatment strategies. You will work in a highly interdisciplinary environment spanning oncology, cell biology, imaging, bioinformatics and machine learning, with
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in securing research funding is essential, as is demonstrable expertise in complex modelling techniques such as machine learning, network neuroscience, or related computational approaches. You will
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of References Allowed Keywords statistics, biostatistics, computer science, economics, health care policy, causal inference, machine learning
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processes that use data-driven machine learning. Given the span of the IN-CYPHER programme, we are seeking multiple motivated research fellows. Unique in its scope, we are developing technologies that span
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combines HPC service provision and R&D into both computer and computational science (life, earth and engineering sciences) under one roof, and currently has over 1000 staff from 60 countries. Look at the BSC