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Field
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in physics, electrical/electronic engineering, computer science, mathematics, or a related field Strong background in machine learning, particularly deep learning and optimization methods Excellent
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focus. Example learning problems include exposome and dynamic exposome modeling, learning in timeseries and spatial data, and hybrid deep learning-causal modeling. The successful applicant should have
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with Unity or XR development, deep learning frameworks (e.g., PyTorch, TensorFlow), or real-time sensor data processing is considered a strong merit. Prior experience in reinforcement learning
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electronic health record (EHR) data; apply ML methods (especially deep learning methods) to solve critical medical problems. Implement methods into software that meets research needs, manage and update source
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social justice? Are you interested in examining the deep existential impacts of Long Covid on patients? Then we would encourage you to apply for this PhD position, wherein you will have the opportunity
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 20 days ago
. [8] Michaela Blott, Thomas B Preußer, Nicholas J Fraser, Giulio Gambardella, Kenneth O’brien, Yaman Umuroglu, Miriam Leeser, and Kees Vissers. FINN-R: An end-to-end deep-learning framework for fast
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and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
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may also be appropriate for research projects requiring long-term strategies of building trust to gain access to the object of research. Fieldwork may consist of deep immersion in one place or research
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Prof. João Pereira dos Santos, Assistant Professor 4. Fellowship Activities Plan: Portugal is currently facing a deep housing paradox: more than 723,000 dwellings were declared vacant in the 2021 Census
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efficient for medicine? If the answer is yes, please continue reading! Join our team! We are looking for a PhD student to work on the topic of shape analysis for medical imaging, tailored for deep learning