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Field
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: A MSc degree (or equivalent) in Biomedical Engineering, Mechanical Engineering, Applied Mathematics, or related engineering/scientific fields. A strong affinity for complex theoretical concepts in
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). These instruments exploit contrast variation, a powerful neutron technique, to resolve molecular-scale structures at complex interfaces invisible to other probes. The aim of the PhD project is to understand
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Analytical Food Chemistry at Technical University of Munich | Freising, Bayern | Germany | about 2 months ago
a Research Infrastructure? No Offer Description About the MSCA project MICROSUNSET is a Marie Sklodowska-Curie Actions Doctoral Network (MSCA-DN) funded by the European Union, in which we have 12 open
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Analytical Food Chemistry at Technical University of Munich | Freising, Bayern | Germany | about 2 months ago
a Research Infrastructure? No Offer Description About the MSCA project MICROSUNSET is a Marie Sklodowska-Curie Actions Doctoral Network (MSCA-DN) funded by the European Union, in which we have 12 open
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lightweight AI models suitable for real-time execution on constrained platforms using techniques such as model compression, quantization, and hardware-aware neural network design. Investigating mechanisms
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complex biological systems. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable
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to modern-day technologies and the net-zero transition. Despite their strategic importance, the UK remains heavily dependent on fragile global supply chains and primary mining routes with significant
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This is a four-year (1+3 MRes/PhD) studentship funded through the Cambridge EPSRC Centre for Doctoral Training in Future Infrastructure and Built Environment: Unlocking Net Zero (FIBE3 CDT). Further
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, transportation networks, and water treatment plants, increasingly rely on AI-driven decision-making for efficiency and autonomy. However, these systems face unique safety challenges. Real-world conditions
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safer, more reliable, and more sustainable renewable energy systems. You are driven by scientific curiosity, enjoy working with complex multi-physics models, and are eager to advance probabilistic methods