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observational data of non-CO2 greenhouse and ozone-depleting gases (e.g., N2 O, CFCs, HFCs), and to extract diagnostic insights from instrument performance indicators, using machine learning methods. Additional
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transformation, machine learning, and data analysis applied in logistics and supply chain management; support graduate-level teaching activities for both the Supply Chain Management residential (SCMr) and Supply
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Physics or an adjacent field, such as Mathematics, completed by the start of the appointment Knowledge of High Energy Theory and Machine Learning, as usually acquired through a PhD in Physics or a related
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, Security, Cryptography, or a related field) and a relevant MSc degree (e.g., Computer Science, Software Engineering, Machine Learning, Artificial Intelligence, Computational Linguistics, or a related field
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 3 months ago
substantial intellectual independence and opportunities to collaborate closely with machine learning scientists developing predictive models of cellular function. Machine learning experience is not required
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
experimental stem cell biology, human and mouse model systems, and machine learning approaches for phenotyping, target discovery, and therapeutic evaluation. Will be hired by the MIT Jameel Clinic for Machine
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skills, and proficiency in machine learning frameworks such as Python, C/C++, TensorFlow, and PyTorch. 4. Hands-on experience with ultrasound systems, particularly Verasonics or similar platforms is
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-quality research results in top-tier venues spanning machine learning, reinforcement learning, embodied AI, and AI in education (e.g., NeurIPS, ICML, ICLR, ACL, CoRL, IEEE ICRA/IROS, AIED, EAAAI
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modeling and probabilistic machine learning, tackling problems that arise in molecular systems and heterogeneous materials. Eine Postdoktorandenstelle im Bereich physik-informiertes generatives Modellieren
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noise, a prototype cryogenic interferometer, using machine learning for nonlinear feedback control, devising techniques to quell opto-mechanical instabilities that can disable the interferometers, and