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involved in projects that handle big-data research, bundling genetics, multi-omics, biomarker, clinical, and histopathological data, to better understand Alzheimer’s disease and related dementias. Overall
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
, or other novel/emerging pollutants - Developing / implementing advance machine learning algorithms for environmental datasets - Attention to detail and careful documentation of work products such as How
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from vascular lesions and blood, combined with genetic, clinical/epidemiological and imaging parameters from patients. We also perform in depth functional studies in animal and cell culture models
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: January 19, 2026 (for full consideration) Apply online at AJO: https://academicjobsonline.org/ajo/jobs/31255 The Center for Data Science for Enterprise & Society at Cornell University seeks to recruit
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an international call to hire 1 (one) Researcher, in form of an Unfixed-Term Contract and at full-time under the Research Project “SmartADC Design of a ultra high-speed time-interleaved ADC using genetic algorithms
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generation initiative. Our laboratory has expertise in deep learning, including deep reinforcement learning, large language models, and the theory of deep learning. The candidate will develop DRL algorithms
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. Occupational Summary Dr. Wen is seeking to hire a part-time (20-30 hours) research technician to support the development of an software algorithm for the project “Measuring Ocular Pulse Amplitude with Fixed
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, bioinformatics pipeline development, and computational analysis of large-scale biobank datasets to study cardiovascular disease genetics. Primary responsibilities include analyzing common and rare genetic
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optimize algorithms for data-intensive research. Deploy and maintain systems in both simulated environments and on physical hardware. Diagnose and resolve complex system and software issues. Execute feature
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research activities, assists in preparing human subjects protocols, manages and analyzes data across multiple projects. Contributes to building traditional statistical models and machine learning algorithms