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expertise in bioelectronics or software simulations, or a strong willingness to acquire it, alongside solid knowledge of electrochemistry and materials chemistry Candidates should be eager to collaborate
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Factory and the IIM Seminar Room. The Schumpeter Laboratory for Innovation offers state-of-the-art technologies in physical and digital prototyping. The LEAD Factory is a flexible and Learning- and Model
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dynamics to longer-term fluctuations driven by biological factors and learning. (3) Design and coordinate a large-scale data collection using a measurement-burst EMA approach to test the models and address
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PhD student position on development of innovative bifunctional oxygen electrodes for SOC technology.
letter and bachelor/master transcripts to irecjobs@irec.cat , mtorrell@irec.cat (Marc Torrell) and atarancon@irec.cat (Albert Tarancón) with the name on the subject 2026/45. Where to apply E-mail
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macro- scales at IJL, and to train machine learning models to predict the microstructure evolution at larger scales and longer times at SIMAP lab and Laboratoire Analyse et Modélisation pour la Biologie
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PhD candidate on Interprofessional Learning and Team Resilience through the Electronic Health Record
team resilience. PhD candidate on Interprofessional Learning and Team Resilience through the Electronic Health Record Our goal: You will contribute to the E-PLUS project (Epic and interprofessional
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the domain of Professional Training & Development & Lifelong Learning at O2L, we are looking for a PhD candidate with an interest in adult education and lifelong learning. Specifically, you will contribute
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applied methodologies in Data and Image Analysis, Computational Imaging, Statistical Learning, Uncertainty Quantification, Robust Estimation, and Deep Neural Networks. The group combines expertise in
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Bayesian optimization and other active learning techniques to guide experimental efforts by identifying optimal chemical compositions and processing conditions of membranes that maximize both selectivity and
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, the candidate will help the team on the following tasks and research areas : - improve integration of the framework with learning/inference framework (PyTorch, Keras, AIDGE, ...) - improve implementations of low