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, ML, and data science, and apply them to research projects. Document development processes, models, and algorithms for future reference and reproducibility. Ensure compliance with data privacy and
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Responsibilities: Development of stochastic and analytical methods for nonlinear partial differential equations Implementation of relevant numerical experiments using deep learning algorithms Job Requirements: PhD
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one statistical software package (e.g., SPSS, R , Stata, M plus) Proficient or knowledge with Machine Learning algorithms Experience in working with databases. Experience with Qualtrics Familiar with
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(networked) dynamical systems" (broadly defined) and there is ample room for exploring sub-topics depending on the interest of the candidate. The focus will be on deriving efficient algorithms with provable
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applicant is expected to be familiar with fully homomorphic encryption and its applications in AI models. Key Responsibilities: Conduct research into trust technologies testing – translating algorithms, tools
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. The focus will be on deriving efficient algorithms with provable statistical guarantees, using tools from: high-dimensional statistics, optimization, probability theory, approximation theory etc
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or Mathematics or Statistics with a strong background in one or more of the following: AI, machine learning, Bayesian statistics, programming languages, logic and algorithms, formal methods, probability and
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the values of fairness, safety, and privacy in digital technologies. Key Responsibilities: Conduct research into trust technologies testing – translating algorithms, tools, and frameworks into working
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teams (>10 Pax) Preferred Proficient or knowledge with Machine Learning algorithms Experience in conducting neuroimaging studies in educational contexts Experience in working with databases