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, and data analysis. Communicates effectively in English, both orally and in writing. Is motivated, collaborative, detail-oriented, and curious to learn. Is interested in mentoring or collaborating with
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in computational methods, particularly those with backgrounds in machine learning, artificial intelligence (AI), statistics, bioinformatics, or analysis-acceleration technologies. Candidates should
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the European Research Council - ERC COG 101088763. The work for this position is in the area of Machine Learning and Natural Language Processing. We are offering We offer a challenging position with the
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, or a related field) A relevant MSc degree (e.g., Computer Science, Software Engineering, Machine Learning, Artificial Intelligence, Computational Linguistics, or a related field) Strong skills in machine
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, applications of machine learning to particle phenomenology, and lattice QCD, both within the Standard Model and beyond. The particle physics phenomenology group members are: J. F. Kamenik (head), B. Bajc, S
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, machine learning, statistics and programming skills (R and Python) is preferred. Record of peer-reviewed publications. Knowledge in one or more of the following areas is desirable: single-cell profiling
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competitive ERC. The project focuses on the development of a first-principles, machine-learning-accelerated computational framework for modelling polymorphism, anharmonicity, and electron–phonon interactions in
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want to hear from you! Your Job: Work on a wide range of computer vision and machine learning methods and applications focusing on the aspects outlined above, inspired by the needs of societally relevant
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research teams that include faculty, graduate students, and undergraduate students. One student’s research used machine learning to solve physics problems, while another’s helped create a data science
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Postdoc Appointment Term: 2 year renewable Appointment Start Date: As early as summer 2025 Group or Departmental Website: http://www.staarlab.com (link is external) How to Submit Application Materials