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construction, and a robust foundation in statistical spectral analysis, including familiarity with (or strong interest in) chemometrics and/or machine learning algorithms. Job requirements The Ideal Candidate
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the improvement of the wetting/during algorithm in TELEMAC2D, including the effects of vegetation. Modelling the SPM turbidity in 3D (using TELEMAC3D) in front of the Belgian coast, validated with 3D remote sensing
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researcher in algorithmic game theory and/or online learning, working with Prof. Celli at BIDSA and the Department of Computing Sciences. The project studies how multiple machine learning algorithms interact
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. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration with the Department
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independently under the mentorship of the project director, Prof. Simon DeDeo, and a board of advisors in mathematics (Akshay Venkatesh, Michael Harris, Simon Rubinstein-Salzedo), computer science (Dana Randall
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Institution: Technical University of Munich (TUM), Germany – 12 months Industrial Partner: GIM Robotics, Finland – 24 months Supervisors: Prof. Achim Lilienthal (TUM), Dr. Jose Peralta (GIM Robotics) Target
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fluid-structure interaction (FSI); - Development of techniques for deforming fluid domains, including Chimera techniques. The doctoral research needs to realize algorithmic improvements in the topics
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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job The individual will perform multi-dimensional physiological and biomarker analyses collected from multiple datasets from
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on rapid and accurate quantification of disasters using remote sensing and space geodesy. They will also advance InSAR processing algorithms to optimise change detection capability in Southeast Asia, where
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development of (open source) tools and algorithms for numerical simulations; o supervise PhD students conducting research in the field of this vacancy; o take responsibility for project coordination