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omics and big-data sets using statistical and machine learning approaches. The details on responsibilities, obligations and rights of the position see: https://www.osi.lv/en/vacancies/ Provisional start
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
1801P.01460.1.06 LARSYS/ISR BASE 2025-2029 - LASEEB LAB/ISR, financed by national funds through FCT/MCTES (PIDDAC Workplan: The scholarship holder will acquire simultaneous EEG/fMRI imaging from healthy
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the following ones. Exploration of active auditing techniques for large machine learning models, use of reinforcement learning, potential application to recommender systems. The PhD will mainly investigate
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of everyday life. This project aims to change that by developing AI-driven methods to assess wellbeing through video-based sentiment analyses. As a PhD student, you will develop and refine machine learning
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. Machine learning will assist in artifact correction, segmentation, and material classification. By combining experimental imaging, simulation, and data-driven interpretation, this approach will deliver high
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physical). Solid background in programming and experience with machine learning. Knowledge of participatory design and co-creation methodologies. Ability to learn independently and passion for research
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at the interface of machine learning, statistics, and live-cell biology. The position is co-supervised by Prof. Olivier Pertz (Cell Biology) and Prof. David Ginsbourger (Statistics), and the student will be equally
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senior members in the lab, and at the same time to play an active role in shaping and creating inspiring research and working environment. In line with our and Uni Basel values (https://www.unibas.ch/en
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early detection is a need that needs to be addressed using advanced sensors. The candidate will apply machine learning and IA methods to anticipate the evolution of the discharges. This project aims
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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code