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Field
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experience with R (possibly also Stata, Python or other statistical software) Excellent oral and written English-language communication skills Established record of population health research and scholarship
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that demonstrably accelerate scientific discovery. Architect and operate federated and collaborative learning experiments spanning multiple sites (national labs, universities, industry) with secure aggregation
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electronics. Experience in C/C++, Matlab, and Python programming. Experience in power systems software like PSCAD, PSS/e. Preferred Qualifications: Experience in real-time simulation hardware like Opal-RT and
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monitoring. The position is planned to start in January 2026. About us At the Department of Electrical Engineering (E2), we conduct internationally recognized research across multiple areas, including
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generate a new understanding of MoSS. These advances will have applications across multiple sectors, including pharmaceuticals, agrochemicals, and food industries. There are multiple opportunities
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related field. Documented expertise in machine learning and time-series modelling (e.g. LSTM, XGBoost, CNN). Strong programming skills in languages such as Python and R. Experience with phenotyping data
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testing data. Knowledge of scientific software in python (numpy, scipy, pandas) or related data analysis suite. Record of productive and creative research as demonstrated by publications and conference
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, characterisation and modelling to study and generate a new understanding of MoSS. These advances will have applications across multiple sectors, including pharmaceuticals, agrochemicals, and food industries
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
(chromatin accessibility, histone modifications), and the environment (metabolome, intestinal microbiome) in the onset and progression of the complex diseases. We have performed multiple functional genomics
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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