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Field
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the use of machine learning and AI approaches • Integration of proteomics with genetic data via MR, coloc and FUSION to identify causal and druggable targets Requirements • The successful applicant will
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broad spectrum of fields, from core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes
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to apply Website https://www.academictransfer.com/en/jobs/359291/postdoc-in-machine-learning-and… Requirements Specific Requirements We will base our selection on the following components: a PhD degree in an
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. Required PhD in Computer Science / AI / Machine Learning Strong publication record in AI, ML systems, or related areas Strong programming skills in Python, C/C++ and experience with PyTorch, TensorFlow, JAX
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in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses on methodological development in cryo
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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, Higgs physics, particle dynamics in the early Universe, collider phenomenology, applications of machine learning to particle phenomenology, and lattice QCD, both within the Standard Model and beyond
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of Barcelona; Particle Physics Phenomenology group. Main responsibilities / tasks: 1. Develop anomaly detection methods using Machine Learning and Simulation-Based Inference for high-dimensional parameter spaces
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your application: A doctoral degree in automatic control, electrical engineering, computational materials science or related. Research experience in battery tests, machine learning, data-driven
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*• Experience in Python or another programming language (projects, GitHub repositories, courses, scientific use).• Training or experience in machine learning and data science applied to environmental or energy