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Field
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density) influence energy dissipation develop mathematical models to predict and explain these effects collect and analyse data, including with the use of machine learning use this knowledge to design
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operates in English, strong English skills are essential. Further project details will be discussed during the interview. The anticipated start date is no later than February 2026. Profile PhD degree in
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profile: A PhD in AI, preferably at the interface of information retrieval and machine learning; Research background in generative information retrieval, with publications in the leading venues relevant
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Professor of Chemistry, affiliated with the NanoTech Institute. The successful applicant must have a recognized research record, a strong record of collaborative research, ability to acquire external grant
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Salary: $62,500 annually Special Instructions: A cover letter and resume are strongly recommended. You may upload these in the CV/Resume section. Required Education and Experience Appropriate PhD in a
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is looking for a highly motivated and independent individual to work as a Postdoctoral Associate. This position is for a post-PhD trainee preparing for a research scientist career path. The planned
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density) influence energy dissipation develop mathematical models to predict and explain these effects collect and analyse data, including with the use of machine learning use this knowledge to design
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ocean environments, ensure safe and sustainable operations. Our activities are centered on numerical modelling (e.g. CFD, FEA, FSI, optimization, machine learning), but also include experiments and real
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, machine learning & data mining (#65), software engineering (#71), mobile computing (#18), and computer security (#88). In the last few years, students and faculty in the department have received
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and analysis Gaussian processes, random functions, rare events, harmonic analysis Shira Faigenbaum-Golovin Manifold learning, shape space analysis, machine learning, mathematics of data