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relevant areas (e.g., software engineering, cybersecurity, program analysis, machine learning), as evidenced by transcripts. Relevant professional or research experience in software security, static analysis
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
: The scholarship holder will acquire electrophysiological data (EEG; ECG; EMG) from healthy and/or stroke patients, involving brain-computer interfacing with VR training in a lab and in a clinical environment
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LevelPhD or equivalent Skills/Qualifications PhD (or equivalent) in mathematics or computer and information sciences or information and communication technology, at least 2 years of documented experience in
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will apply machine learning — in particular physics-constrained symbolic regression — to discover compact analytical spin-Hamiltonians and their parameter dependencies. These Hamiltonians will feed large
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with experimentalists to validate predictions made by their machine-learning models and drive wet-lab discoveries. The candidate may also have opportunities to work with research software engineers
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About the Opportunity The Lecturer will teach introductory courses in architectural drawing, sketching, studio design, computer modeling, architectural history, technology, or project case studies
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solver who wants to be part of a dynamic team. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/human-organs-on-chips/ What you’ll do: Independently
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for next-generation (6G) communication systems. The project focuses on integrating Artificial Intelligence (AI) and Machine Learning (ML) capabilities into distributed cloud-edge infrastructures to enable
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technology and research from across the university. This position works closely with the Executive Director and the Venture Associate to develop and manage a robust pipeline of faculty, researchers, PhD
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computational engineering, mathematics, computer science, physics, engineering or a related field Strong background in numerical methods and machine learning Proficiency in at least one programming language