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Field
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, geometric/topological/algebraic data analysis, geometric/topological deep learning, Math for AI, categorical deep learning, sheaf neural networks, Perform data preprocessing, algorithm/method/model design
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: Develop and apply evolutionary algorithms to jointly optimize both the robot’s morphology and autonomy, and apply quality-diversity methods to discover a wide range of high-performing designs. Work
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perform 3D single-particle tracking and establish pipelines to characterise the particle motion using a combination of established tracking algorithms and machine-learning-based approaches. Additionally
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use of data and algorithms. Excellent written and verbal communication skills and ability to communicate effectively with a variety of different stakeholders, e.g., academics, business executives
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algorithms, and non-inferiority margin derivation methodologies. You will develop proficiency in regulatory database management, systematic data extraction from NDA submissions, and implementation of network
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learner, analytical thinker, creative, "hands-on", team-player. ? Experience with computational analysis, algorithm development and statistics. ? Proficiency in at least one modern programming language
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electricity markets; conducting research in nonlinear, convex, and mixed-integer nonlinear optimization; designing and implementing advanced computational and algorithmic solutions; performing computational
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unify programs and curricula in data science with an initial emphasis on questions grounded in data that are generated by human activity, including computational social science (e.g., algorithmic
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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of novel indoor localization and tracking methods, algorithms, and systems ? Evaluating the performance of such methods, algorithms, and systems via modeling and simulation ? Performance evaluation via