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Field
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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code
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that support the unit for area protection and marine spatial planning, as well as operations at SLU Aqua. Your profile You have documented expertise in marine ecology and computer vision and machine learning
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conferences and workshops. The Research Assistant Professor may be asked to teach (or may ask to teach) but that is neither required nor guaranteed. Qualifications Applicants must have a Ph.D. in Economics or
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for this position, however, we are still accepting applications from other qualified candidates. Position Summary Our goal is to identify computational principles underlying learning and decision-making behavior and
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for robotics, perception, prediction Computer vision and data acquisition System modelling and control JUNIOR RESEARCHER – Responsibilities Participate in R&D tasks across ongoing projects Support experimental
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Your Job: In this position, you will be an active part of our "Simulation and Data Lab Applied Machine Learning". Within national and European projects, you will drive the development of cutting
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cytometry). 25%: Project Management Mouse colony and research project management. 15%: Data Collection and Distribution Utilize basic computer skills to log data, conduct routine computer analysis of research
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) data. We also analyse macaque electrophysiology data obtained through collaborations. We use machine learning techniques for data analysis and computational modelling with a special interest in
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+to+apply#Howtoapply-Eligibility ) a Master’s degree in Artificial Intelligence, Machine Learning, Computer Science, Cognitive Science, Psychology or a related field excellent knowledge in AI and at least one
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++, Python, and JavaScript languages, multi- and many-core SoC, RISC-V, hardware synthesis, hardware-software co-design, (meta-heuristic) optimization algorithms, machine learning frameworks, (bonus topics