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areas: Artificial Intelligence/Machine Learning for Drug Discovery: Designing and applying machine learning models to identify new drug targets, predicting drug efficacy and toxicity, and optimizing small
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environment as part of the Oxford Motor Neuron Disease Centre and will be based in the Kavli Institute for Nanoscience Discovery. Using patient iPSC-neurons, our group aims to determine regulatory pathways
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methods (e.g., SEM, XPS, in-situ XRD) to study sensor performance and degradation mechanisms. Contribute to system-level optimization of sensor signal quality and environmental stability. Prepare research
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the initial phase, you will develop and optimize physical and numerical models describing the electron optics of the complete probe-forming column, including the multi-beam generation unit, imaging lenses
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three main phases. In the initial phase, you will develop and optimize physical and numerical models describing the electron optics of the complete probe-forming column, including the multi-beam
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toxicity, and optimizing small molecules and biopharmaceutical design. Quantum Computing in Pharmacology: Using quantum mechanics and quantum computing to model complex molecular interactions and simulate
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switching behavior in hBN, using plasma treatments, electrical and spectroscopic characterization, and first-principles modeling. The optimized devices will be integrated into crossbar arrays to demonstrate
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supported research experience with top-caliber scientists and access to state-of-the- art instrumentation. The CFN mission is advancing nanoscience through frontier fundamental research and technique
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of Microtechnology and Nanoscience (MC2) at Chalmers University of Technology, is a highly interdisciplinary research environment led by Professor Johan Liu. The lab focuses on pioneering solutions at the interface
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performance testing (e.g., polarization curves, EIS). Design and execute experiments for materials optimization and degradation analysis. Maintain and operate laboratory equipment, including potentiostats