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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 4 days ago
LARSYS/ISR BASE 2025-2029 - LASEEB LAB/ISR, financed by national funds through FCT/MCTES (PIDDAC Workplan: Implement discrete‑time fractional‑order state‑space models of anesthetic‑induced brain dynamics
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We are seeking a Research Fellow to perform research on deployment of machine-learned models for health analytics on distributed IoT/edge/cloud systems using transprecise computing and contribute
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prediction models in Neurology using EEG data via Deep Learning (DL) techniques. In this prospective and longitudinal study, the outcome of interest is cognition over time. This position will be under
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to gender—and demonstrated expertise in advanced statistical methods (e.g., multilevel modelling). The successful candidate will work closely with the Principal Investigator, Dr. Verena Klein, a PhD student
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administrative tasks related directly to the delivery of the research Promotes equality and values diversity acting as a role model and fostering an inclusive working culture Assist in writing papers for high
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of the Fellowship is to develop deeper metallurgical understanding via characterization and modelling to underpin the design of alloys with smaller societal footprints. Three roles are on offer to address
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processes in Australia. The second will involve a climate or biodiversity deliberative assembly based in Europe. Your key responsibilities will be to: document and analyse existing models of MtHR and what is
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epidemiological study designs and biostatistical modelling approaches to a broad range of health and environmental data. The team address policy relevant research with a focus on translating the results
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(e.g., hardware trojans, side-channel exposure). Co-develop testbenches for hardware simulations and chiplet-level threat modelling. Collaborate closely with FPGA and IC prototyping teams to deploy AI
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policy briefings Contribute to development of implementation strategies and evaluation plans Supervise students working on related research themes Contribute to developing and refining models, methods, and