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Field
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research • Deep learning and predictive modeling • Natural language processing and large language models for biomedical data • Drug response prediction and treatment optimization • Biomedical knowledge
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is to understand, develop, and optimize electrochemical reactions under practical, relevant conditions to take a step further in using electrochemistry at industrial scale. Where to apply Website https
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activate spinal networks. This PhD project aims to investigate the underlying mechanisms of rSynES-induced recovery using a mouse model of cervical SCI, through longitudinal assessment of molecular and
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systems, optimizing audio playback levels, and supporting other acoustic interventions to improve occupant comfort and building performance. The research will adopt a human-centered approach, placing
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-to-confidence set conversion' framework recently proposed by the PI (Principal Investigator). The models of interest include deep neural networks with multiple layers and non-linear activations, extending recent
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develop advanced models, algorithms, and control solutions for simulating, optimizing, and operating future integrated energy systems. We address the challenges arising from the increasing integration
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methodologies for evaluating suitable storage sites and optimized lined rock cavern designs; - publish research findings in leading international scientific journals; - present research at national and
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("Advanced Wide Bandgap-based Power Processing and Management for Future Space Exploration") is a Horizon Europe MSCA Doctoral Network Joint Doctorate (DN-JD) initiative developed in collaboration with
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16th August 2026 Languages English English English The Department of Industrial Economics and Technology Management has a vacancy for a PhD Candidate position: Hybrid AI-Optimization for Dynamic and
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at cryogenic conditions: Many advanced technologies — like quantum computers, powerful microscopes, and chip-making tools — require extreme cooling. However, the optimal design of cooling systems at cryogenic