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Field
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for preparing technical reports, papers, graphs and/or records. Responsibilities Conduct research independently and in consultation with the supervisor. Prepare technical reports, papers, graphs and/or records
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and its stakeholders. You should hold a Master’s or PhD (desirable) in Computer Science, Artificial Intelligence, Machine Learning or a closely related field. We are looking for a candidate who has
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( laboratory’s website (https://medicine.ouhsc.edu/academic-departments/biochemistry-and-physiology/faculty/veronica-galvan-hart-phd ) and the laboratory’s web page (https://www.galvanlab.org/). Performs routine
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science and industry. With the Open Research Knowledge Graph (ORKG ), we are working to revolutionise the exchange and use of scientific knowledge in the digital age. The Technische Informationsbibliothek
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(ICPSR). Support faculty with the import, organization, formatting, cleaning, and coding of data. Consult faculty on the selection and application of analytical methods (such as graphing and tabulating
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, molecular biology, and animal work. The expected salary for this position is $68,932 per year. Required scientific background: A PhD degree in life sciences (e.g. biochemistry, cell biology, immunology
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(for example, R, Python, or Matlab). Experience with graph modeling, Bayesian statistics, or causal inference is a plus. The candidate will join an integrated team of computational scientists, molecular
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collaboration with experimental groups, to address questions of biomedical or industrial relevance. The candidate will develop and use machine learning methods (mainly graph neural network architectures
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. Data management skills including development, organization, implementation, and quality control of complex data sets. Data analysis and graphing skills required to prepare data for grant proposals and
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performance analysis, graph-driven deep neural networks, data-efficient machine learning, self-supervised learning, reinforcement learning, online learning, and meta-learning with applications