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Field
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: Artificial Intelligence / Machine Learning Knowledge Representation and NLP methods Clinical Informatics Bioinformatics Biomedical Ontology Public Health Informatics Nursing Informatics Imaging Informatics
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Post Doc Associate This postdoctoral position is funded by an R01 grant (1R01AG082954-01) from the National Institute on Aging in collaboration with Northwestern University. The project is titled
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Position Title: Postdoctoral Research Associate - Biogeochemistry Appointment Type: Post Doc/Trainee Job Description: Summary of Duties and Responsibilities: The Soil Biogeochemistry Lab is seeking
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Post Doctoral Associate The Center for Veterinary Business and Entrepreneurship in Cornell University’s College of Veterinary Medicine seeks a postdoctoral fellow to work with Assistant Professor
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it; as well as have theoretical skills including algorithm implementation/development and data visualization. Experience and interests include designing machine learning pipelines, building web
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Charles Henry Turner Post-doctoral Fellow, Department of Geography & GIS, College of Arts & Sciences
-driven analyses. The fellow will also be expected to design and teach two distinct semester-long courses over the two-year period. Unique to the Turner Post-Doctoral Program is the possibility of a being
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data set to be used for Machine Learning (ML). They will validate a predictive model generated by ML by preparing new samples with ideal monomers and contrasting their properties with predicted values
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models and machine learning. Minimum Qualifications MD or Ph.D. in Basic Science, Health Science, or a related field. No experience required. Preferred Qualifications Experience in epigenetics or gene
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of the post-doc is to study how innovations in AI, especially adaptation of Large Language Models (LLMs) architectures for time-series data, can be used in study of aging, health span, and longevity
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on the development of Bayesian statistical/machine learning methods for the data integration analysis of high-throughput imaging and molecular data (i.e., genome, transcriptome, epigenome, and more). The methods would