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Field
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: The PhD Researcher will be responsible for the development of sustainable inks based on metal oxide nanostructures and two-dimensional (2D) materials, as well as for the optimization of the corresponding
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will develop novel ligands for a validated drug target in acute myeloid leukemia. Building on our promising preliminary results, you will optimize and expand the hit discovery using computer-aided tools
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optimization. In this context, interdisciplinary research is strongly encouraged—particularly collaborations spanning computer science, computational linguistics, cognitive science, and the learning sciences
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awareness (SA), like our work on Situational Graphs (S-Graphs), improve on existing techniques by combining 3D environmental maps with detailed knowledge about objects into a single, optimized model. First
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characterization of optimal target proteins and complexes, involving their recombinant expression and purification in bacterial and eukaryotic systems. Characterization of best dopaminergic cell models (e.g., SH
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and quantum annealing for physics-driven optimization problems is also part of the research portfolio. Detector R&D for future facilities, leveraging Purdue’s infrastructure for detector development
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and image data processing. Specific knowledge related to neural network design, training, and optimization is required. You will be joining a group with core expertise in sensor data analytics from
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The School of Computer Science and Electronic Engineering at the University of Essex hosts research in communications, networking, signal processing and optimisation. The post will be based within
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microbiomes to optimize end-of-life material processing and circular resource recovery. This position will be part of the UT-ORII’s Circular Bioeconomy Systems (CBS) Convergent Research Initiative (CRI
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Manufacturing and/or AI Robotics. Focus areas include: yield/defect causal analysis and XAI; process-variation monitoring and root-cause analysis; intelligent scheduling/dispatching for WIP/throughput (multi