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Field
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Experience developing pipelines and code for gravitational-wave searches and/or parameter estimation Knowledge of advanced Bayesian methods and samplers, machine learning approaches to signal processing
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specialised libraries (TensorFlow, PyTorch, scikit-learn, Pandas). Knowledge of machine and deep learning methods and techniques, including training, adjustment and development of language models and LLMs
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platforms. Experience in development of digital twins or physics-informed machine learning models. Experience in programming (e.g., Python or equivalent) and development of control or data acquisition
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infrastructure (e.g. Observatorio del Roque de los Muchachos) Hands-on training in cutting-edge techniques, from detector R&D to advanced data analysis and machine learning. Attendance to international
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, spectropolarimetric inversion techniques, and machine-learning–based approaches, for the physical interpretation of solar images and spectral profiles. Special consideration will be given to applicants with experience
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=50415 Requirements Research FieldPhysicsEducation LevelPhD or equivalent Skills/Qualifications Advanced skills in Machine Learning and Artificial Intelligence Proficiency in spoken and written English
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, including Machine Learning Interatomic Potentials. • Other research experience will be considered. Personal Competences: • Strong commitment • Attention to detail • Demonstrated ability to work with deadlines
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will develop novel ligands for a validated drug target in acute myeloid leukemia. Building on our promising preliminary results, you will optimize and expand the hit discovery using computer-aided tools
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development of analytical solutions, data analysis and machine learning. Candidates should have a demonstrated record of scientific publications in international journals and participation in conferences
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of Spanish (not required but valued for teaching and policy dissemination in Spain). Experience with AI-based research workflows, machine learning techniques applied to financial data, or modern