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Description Research project: CONTEXT DEPENDENT INTERACTIONS IN COMPLEX SYSTEMS: DYNAMICAL PROCESSES PID2024-158120NB-C22 Exhaustive analysis of bibliographic data bases within the framework of the research
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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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Learning and parameterised quantum circuits. Analysis of multi-omic data for the identification of therapeutic targets. Migration of algorithms from classical simulators to IBM quantum hardware
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projects are continuously developed. Continuous learning and career development pathways. Flexible working hours. 23 days of annual leave plus 9 personal days. Flexible remuneration programme, including meal
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based on neutral atom platforms, exploring both theoretical and experimental domains. Research will span quantum control, quantum-enhanced machine learning, and hybrid quantum-classical computation
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AI4Science project, specifically focusing on the intersection of advanced machine learning and sustainable catalysis discovery. The primary incentive of this Postdoctoral Fellowship is the chance to contribute
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conditions and/or to assess the performance under irradiation of diverse fusion materials candidates. Key responsibilities • Fabrication of coatings (primarily sputtering-based deposition) and process
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the neurovascular space. Knowledge of neurovascular anatomy, acute stroke, endovascular treatments, neuroendovascular devices for the treatment of stroke. Ability to generate machine learning analysis of medical
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Nanotools is a research group based at Vall d’Hebron Hospital (Barcelona, Spain). Our aim is to develop and validate novel detection strategies with diagnostic purposes https://vhir.vallhebron.com/es
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and scientific exploitation of state-of-the-art, ground-based gamma-ray telescopes. As a key member of the MAGIC and CTAO-LST collaborations, the group develops critical hardware, software, and data