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years or a SU PhD scholarship (4+4) for a period of up to four years in Probabilistic Methods in NLP: Representation Learning or AI Alignment provided the necessary funding is available. Where to apply
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The PhD project will involve both (a) developing foundational probabilistic machine learning methodology, and (b) applied collaboration with experimentalists in chemistry and biology. The candidate may have
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Mathematical, Probabilistic and Engineering principles and methods. Familiarity with offshore engineering and wave-wind theories is advantageous. Experience in coding (e.g., Python) and in the use of Structural
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problem-solving skills, with a solid foundation in Mathematical, Probabilistic and Engineering principles and methods. Familiarity with offshore engineering and wave-wind theories is advantageous
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Nonlinear Structural Analysis Strong analytical and technical problem-solving skills, with a solid foundation in Mathematical, Probabilistic and Engineering principles and methods Familiarity with offshore
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, particularly GBS, continuous-variable QC Experience with numerical simulation, statistical estimation, or probabilistic modeling. Programming proficiency (Python, Matlab or C++), especially for numerical
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for realistic haptic control and feedback, real-time agent-based simulation for guiding optimal work task performance. Following smart serious gaming approaches, novel artificial intelligence forecasts human
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experimental and simulation data. Use machine learning techniques to identify trends, forecast behavior, and optimize performance metrics in PtX systems. Publish Research Findings: Disseminate research outcomes