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calculations, sample size determinations and statistical analysis plan. 3. Apply machine learning approaches to integrate diverse datasets collected from study participants to identify subtle differences
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conceptual DFT (linear response function, Fukui functions) or QTAIM theory (delocalization index), and their validation on a set of compounds known from the literature - interfacing a MLIP (Machine-Learned
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on physics analysis and artificial intelligence/machine learning (AI/ML). The successful candidate will contribute to the group’s broad physics program, which includes precision Higgs and Standard
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(analysis/ geometry), applieddifferential geometry and machine learning;•Solid publication record in image analysis, scientific computing or machine learning.•Knowledge and practical experience in at least 3
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in international research visits if needed. We are looking for a highly motivated researcher with: A PhD in machine learning, computer vision, remote sensing, glaciology, climate science, or a related
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) PhD degree (or foreign equivalent) in Electrical Engineering or a closely related field in hand by
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and machine learning applied to data fusion and adapt them to the field of exoplanet characterization. They will develop and maintain the FORMOSA code in coordination with the team of students working
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/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We focus on data-driven models for complex and temporal data
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they are kept fully up to date with progress and difficulties in the research projects. It is essential that you hold a PhD/DPhil in a quantitative discipline (e.g. Statistics, Machine Learning, Biostatistics, AI
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annual base salary for this position is $62,500 - 65,000 depending on the candidate’s experience and qualification. Candidates must have a PhD in urban planning, human-computer interaction, design