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Field
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in C++ and/or Python is expected, and experience in model analysis and parameter optimisation is beneficial. Experience in machine learning and neural networks is desirable. The successful applicant
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: active learning (uncertain cases first), smart sampling, confidence thresholds, gradations (auto-label/review/manual), measurement and decision logic for throughput vs. quality. Proficiency in programming
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. Strong (inter-)national network in field of application. Experience with high-performance computing (HPC) and large datasets. Experience with machine learning applied to geophysical signals. Experience in
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interdisciplinary and experiential learning to join the Source Project , Binghamton University's distinctive first-year research program in the Humanities and Social Sciences. The position begins August, 2026. PhD in
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(25260475) Responsibilities: The Department is recruiting a scholar at the rank of Research Assistant Professor in computational mathematics, machine learning, scientific computing, statistics, and related
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challenges, the school provides a wide variety of topics, from logic in autonomous cyber-physical systems to machine learning in Earth System models. You will have one supervisor from the mathematical sciences
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should hold a Master's degree in Computer Science, Artificial Intelligence, Computational Linguistics, Data Science, or a closely related field Solid background in machine learning and natural
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of Unix systems (GNU Linux) and keen to gain hands-on experience in Networks and systems Machine Learning knowledge is a plus Strong analytical and programming skills are required (Python, Matlab, Golang
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and/or testing of samples. May occasionally instruct others in basic laboratory techniques. Working Conditions: Work is performed on-site in Cambridge, MA. May be required to work with a variety of
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projects of the MQS group. Our recent research has focused on the theory and applications of variational quantum algorithms and quantum machine learning. We also have activity in quantum optics, so