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Integrated Circuits or Automation. Background in computational optics, inverse scattering algorithms, label-free quantitative tomography algorithms, optical simulations, image analysis or machine learning
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hazards, enhancing asset protection, maritime security, emergency preparedness, and societal resilience. The project will leverage advanced AI and machine learning techniques to enable predictive risk
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
, financed by national funds through FCT/MCTES (PIDDAC Workplan: The scholarship holder will acquire electrophysiological data (EEG; ECG; EMG) from healthy and/or stroke patients, involving brain-computer
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interactions with local centres of excellence in artificial intelligence, machine learning, applied mathematics, and computational sciences Application Procedure We accept applications from students of any
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in mathematics and topics related to machine learning. EVALUATION CRITERIA The selection will be based on the following criteria: Academic CV (60%) Previous experience in related projects (20
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of the following areas: robotics, machine learning, robot perception, underwater systems, nonlinear control, system modelling, or autonomous manipulation Strong programming skills and a solid
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 2 months ago
1801P.01158.1.04 and (1801P.01460.1.04) LARSYS/ISR BASE 2025-2029 - SIPG LAB/ISR, financed by national funds through FCT/MCTES Workplan: To develop machine learning approaches to behavior analysis in
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. Experience with programming, modelling, statistical analysis, or the use of data analytics, machine learning or artificial intelligence methods is desirable. Personal qualities Strong ability to follow through
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assessed according to the following weights and criteria: - Criterion 1: Absolute merit of curriculum vitae - Criterion 2: Academic performance in the areas of Machine Learning, Data and Information Fusion
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numerical models and machine learning tools to predict loads, assess structural responses, and identify damage under extreme conditions. By combining computational simulations with data-driven approaches