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methods already make it possible to observe neuronal activity during photoreceptor stimulation in genetically modified animals. These methods, with further developments, could effectively provide
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domains. The successful candidate will: Develop algorithms to model team performance based on interpersonal (e.g., monitoring, communication) and cognitive (e.g., shared mental models) processes. Design an
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of computer science fundamentals including algorithms, data structures, and object-oriented programming. Proficiency in C/C++ or similar language Working with large codebases Containerization (Docker) and building
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Group , a leader in innovative multi-sensor atmospheric remote sensing from ground, airborne, and satellite platforms. Our group develops advanced algorithms and data analysis methods to address
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genetics and genomics, with expanded interests in computational biology, functional genomics, and neuroscience. Example projects within the university and with external partners: • Noncoding Variation in
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Group , a leader in innovative multi-sensor atmospheric remote sensing from ground, airborne, and satellite platforms. Our group develops advanced algorithms and data analysis methods to address
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, Experimental Research, Game Theory, and Artificial Intelligence. Some of the research topics that excite us as a group include: (i) Ethics of AI and Automation; (ii) Social Media Analysis (iii) Algorithmic
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inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic
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or accelerated acquisition and reconstruction algorithms will be highly valued. Instructions Interested candidates should apply via Interfolio link with their CV (including a full list of publications), a
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data management sufficient to create, transform and integrate data in a variety of resolutions and formats. Analysis will include running machine learning algorithms (e.g., Random Forest, CART) and