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Field
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• Develop, consolidate, and optimize fMRI and EEG neurofeedback algorithms. • Design, integrate, and test standalone neurofeedback software (software suites for clinical environments). • Contribute
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construction, and a robust foundation in statistical spectral analysis, including familiarity with (or strong interest in) chemometrics and/or machine learning algorithms. Job requirements The Ideal Candidate
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utilization. The successful candidate will play a significant role in the EU‑funded TIMBERHAUS project (www.timberhaus.eu). Your tasks Develop machine learning models and computer vision algorithms for wood
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machine learning, modeling algorithms, and/or mapping applications. Applicants must have a PhD in ecology, wildlife sciences or geospatial modeling. Additional Information: Salary Information: Commensurate
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-luminosity phase of the LHC. The successful candidate will work in close collaboration with other members of the Particle Physics team, and with members of the Computing, Algorithms and Data team at L2IT
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outcomes. The individual will be expected to develop stimulation strategies and testing algorithms, write code, and develop software. They will do extensive validation and testing, under the supervision
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 19 days ago
is designed for candidates who have completed their PhD within the last two years and have experience as postdocs or industry researchers. This position offers a 12-month term with potential
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econometric modeling, scientific-oriented thinking, communication and team skills, with a PhD in the field of economics, (business) mathematics, (business) informatics, marketing, management. As a member of the
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Foundation RECRUIT grant ("Data Management, Algorithms, & Machine Learning for Emerging Problems in Large Networks – with Interdisciplinary Applications in Life & Health Sciences". NNF22OC0072415
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algorithmic fairness Formulation of new problems and research directions and translating topical issues into algorithmic problems Designing new algorithms and investigating their performance on synthetic and