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Field
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environments. Collaborate with multidisciplinary teams to optimize material–device interfaces and sensor architecture. Assist in the prototyping of sensor devices and contribute to the optimization
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photocatalytic degradation of Per- and Polyfluoroalkyl Substances (PFAS) with optimized COFs Look for necessary collaborations with internal or external collaborators (e.g. theoretical modelling and advanced
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addresses major limitations in surgical force sensing and has strong potential for commercialization and clinical impact. Key Responsibilities Redesign and optimize a fiber-optic (FBG-based) force sensor
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processes and develop innovative tools in cell biology. Key Responsibilities: Conduct experimental research using quantitative biochemistry, biophysics, and cell biology. Develop and optimize advanced
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. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with
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; analyze and interpret data Apply data to the iterative design of optimized chemical probes suitable for cellular and in vivo pharmacological studies Maintain accurate lab records and documentation
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collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond
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decision-making and research findings. Qualifications & Competencies: Minimally a PhD degree in Artificial Intelligence, Computer Science, Optimization, or a related field. Strong foundation in multi-agent
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Apply Now Job Summary In this position, the candidates will learn strategies and techniques for LC-MS analysis, drug optimization and lead drug candidate selection, pharmacokinetics and drug
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and development in the chemical conversion and valorization of hazardous waste streams, focusing on complex, reactive materials. Involves process design, optimization, and scale-up, including reaction