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Field
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exciting opportunities for machine learning to address outstanding biological questions. The postdoc to be recruited will be working on the development of machine learning methods for single-cell data. In
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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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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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sciences, computer science, machine learning, and education research. Research Themes The research themes identified for the NTO postdoc include, but are not limited to, the following: Developing
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, Machine Learning , Neutrino , Neutrino physics and Astrophysics , Phenomenology , Quantum Field Theory , Theoretical Particle Physics , theory , Lattice QCD Appl Deadline: 2025/12/02 04:59 AM
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, dynamical systems, statistical machine learning, and neural time-series data. The goal is to better understand principles and mechanisms underlying distributed brain network computations through the dual
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UnitedKingdomTime) Position Description: Apply Position Description We invite talented and motivated applicants for PhD and Postdoc positions in the group of Haowei Xu (https://www.haoweixu.com/ ) at the Department
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are now seeking postdocs to join the Institute and its wider research community. We welcome applications across all areas of machine learning, artificial intelligence, and related fields. Your research can
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join the group to develop AI and machine learning based software to assist clinical workflow and pre-clinical studies. Required Qualifications: Ph.D. in a physical science or engineering field Strong
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must be no earlier than 2024. You must have at least one first-author publication published by the time of starting the Postdoc. Application Please apply online at https://cemm.onlyfy.jobs/job/7k2624z5