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qualification in Genetics, Bioinformatics, Computer science, Data science, Statistical Genomics or a related discipline involving the interrogation of ‘omics’ datasets. Hands-on experience with large-scale human
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 2 months ago
will develop detailed lifecycle assessments and technoeconomic analyses of the pyrolysis process and for large-scale end-uses of the co-produced solid carbon. The geologic hydrogen project will develop
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develop innovative solutions based on the analysis of urban data (big data, IoT, GIS) to monitor and improve public health. You will contribute to modeling smart cities with a focus on health and designing
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management tools. This role involves designing and executing large-scale epidemiological studies using EHR data, overseeing clinical data annotation/processing from public and Hospital Authority sources, and
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laboratories The candidate will also have immediate access to brain PET data acquired from multiple universities, including Stony Brook. This includes large (>30 participants) datasets examining
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will work on multiple projects funded by NIH/NHGRI. The objective of the position is to develop novel statistical methods and computer software and analyze large scale biological data from biobanks
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Requisition Details GENERAL REQUISITION INFORMATION EEO Statement: UNMC is an Equal Employment Opportunity Employer, including an equal opportunity employer of protected veterans and individuals
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sciences and energy; social sciences; arts and humanities; and computer and information sciences. The Research Foundation, a private, not-for-profit corporation, is an employer separate from both SUNY and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 7 days ago
Posting Information Posting Details Department Biology - 318200 Posting Open Date 08/01/2025 Application Deadline 08/21/2025 Open Until Filled No Position Type Postdoctoral Scholar Position Title
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and brain that explain vision loss, building on our previously-developed method linking clinical, neural and behavioral data (Allen et al., 2018; Miller et al., 2019; Pedersini et al., 2023). We combine