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a unique opportunity to work in a cutting-edge, interdisciplinary environment, leveraging a novel in-vitro model of the human uterus and/or cutting edges machine learning techniques to make
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and experimentalists working across species as part of SCENE The Tolias Lab fuses large‑scale systems neuroscience with machine learning to derive principled models of cortical computation. Our newly
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degree in biomedical data science, computational biology, genetics, bioinformatics, machine learning, computer science, statistics, engineering, medicine, or a related field. Strong candidates may have
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designing machine learning pipelines, building web applications or tools, and creating and maintaining visualization dashboards. Trainees should be comfortable with: · SQL, R, and Python
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. The fellow will also work closely with SCEC Senior Machine Learning Engineer Dr. Lauren Klein Dubin, who will provide day-to-day supervision of the fellow's technical work. The fellow will have opportunities
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Expertise in machine learning, including building and deploying prediction models Strong data science coding skills in programs and languages such as Python, R, Stata, and SQL Experience with research in
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Medicine are seeking to appoint a Postdoctoral Research Fellow to join a project developing and validating deep learning computer vision models to classify mosquito breeding habitat on very high-resolution
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ability to quickly learn and master various computer programs. Strong record of peer-reviewed publications. A PhD, MD or equivalent with prior relevant training in Immunology, Biology, Bioinformatics
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). Experience applying machine learning or AI methods in these fields is an advantage. The ideal candidate should also be comfortable structuring, linking, and analyzing large datasets that include dense
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QUALIFICATIONS: PhD in computer science, electrical/biomedical engineering, statistics, applied mathematics, or a related field. Strong track record in machine learning/deep learning with imaging data