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, Physics , quant-ph , Quantum Science + Quantum Information Science + Quantum Optics + Theoretical Physics , Quantum Sensors , Theoretical Particle Physics , Theoretical Physics, HEP-Phenomenology (hep-ph
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Infrastructure? No Offer Description Research line: Learning in single cells through dynamical internal representations. Job description: Develop theory, models and algorithms for identifying molecular encodings
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alarm protocols; experience in sensor deployment/SCADA and data processing. Ability to optimize regeneration systems and integrate them into service networks; knowledge of EU regulations on water reuse
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plays an important role in the commissioning, operations and upgrade of the interferometer. For the latter, IFAE is leading the construction of new baffles instrumented with photo sensors around the test
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of auditory stimuli and creation of stimulation sequences 5) Implementation of pilot studies in adults and infants 6) Programming analysis algorithms for FFR, MMN and statistical learning, based on spectral and
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-DIGITALEMERGING)" with the functions of junior research staff of group A, subgroup A1. Specific Development of distributed fibre sensors compatible with telecommunications networks. An important part of the work
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optimiser that accelerates both workflow efficiency and materials discovery. Main Tasks and responsibilities: Own the optimiser: design, implement, and tune heuristic/metaheuristic algorithms (e.g
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pathways, including deactivation processes. Screening and fine-tuning catalysts to enhance performance. Developing workflows and machine learning algorithms to accelerate catalyst design (optional). Group
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. Developing workflows and machine learning algorithms to accelerate catalyst design (optional). Group: Atomistic & Molecular Modelling for Catalysis Group Requirements Specific Requirements PhD in Chemistry
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: Design, implementation and testing of new methods and algorithms so that SIESTA can harness the compute power of the latest generation of (pre-)exascale architectures and tackle novel scientific challenges