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data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. The applicant is expected to develop and apply data-driven and machine learning-based methods
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, and written communication skills evidenced by a publication record in the area of control theory, mathematical optimization, AI, or machine learning. Preferred Qualifications: Publication record in
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develop methods to disentangle dynamic, multiscale ecological signals from large, heterogenous observational data. This work lies at the interface of statistics, machine learning/AI, ecology, and
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related field Strong background in data analysis, particularly with behavior data, functional ultrasound (fUS) or other neuroimaging modalities Proficiency in statistical analysis, machine learning, and
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and resistance. Through close collaboration between laboratory and clinical teams, our work bridges mechanistic immunology with real-world patient outcomes. To learn more about Hosoya Lab - https
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Experience in machine learning, math, and programming. LanguagesENGLISHLevelGood Additional Information Work Location(s) Number of offers available1Company/InstituteUniverCountryBrazilState
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University community. Please visit their website to learn more. Special Instructions to Applicants provide 3 references Quick Link for Internal Postings https://www.auemployment.com/postings/44281
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profile for their ideal candidates are described as follows. PREMAL is a project focused on privacy-preserving machine learning using FHE. The project will investigate trade-offs between accuracy, time, and
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and advanced attendees Schedule Flexibility with work schedule Compensation Grade LOA https://www.unr.edu/hr/compensation-evaluation/salary-schedules/loa-and-postdoc Exempt Yes Full-Time Equivalent 0.0
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all over the world, we work together to develop solutions for the global challenges of today and tomorrow. Where to apply Website https://academicpositions.com/ad/eth-zurich/2026/postdoc-position-in