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Do you want to develop your research and teaching in an environment where collaboration with industry and society is a natural part of the work? With us, you will collaborate with dedicated
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Research Infrastructure? No Offer Description Do you want to develop your research and teaching in an environment where collaboration with industry and society is a natural part of the work? With us, you
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interdisciplinary team, the candidate will work closely with both the Q-NEXT Argonne Quantum Foundry along with the Quantum Metamaterials group within the Materials Science Division at Argonne National Laboratory
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biomarkers and quantitative imaging methodologies. Job Description: Job Duties Outlined: Research Overview: Work with PI/faculty mentor to develop, optimize, and apply advanced preclinical imaging techniques
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experimentation, modeling, simulation, and optimization of chemical processes. The successful candidate will work on the development of advanced process models combining experimental investigations with
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), working in 10 research groups and 3 technical platforms. As part of the CoCat-Light project, funded by the French National Research Agency (ANR), we are recruiting a post-doctoral researcher in organic
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experimental work in chemical or process engineering (desirable) Knowledge of process optimization, parameter estimation, or control methods is a plus Programming experience in MATLAB and/or Python Familiarity
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modeling and optimization for metasurface design, integrated with other optical components. Inverse design of optical components such as metasurface photonic-crystal unit cells or VCSELs. Collaborate
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experiments to investigate the activity and specificity of selected proteases. 3. Advanced fluorescence measurements and quantitative imaging Performing and optimizing fluorescence-based measurements, including
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well as performing biochemical experiments to investigate the activity and specificity of selected proteases. 3. Advanced fluorescence measurements and quantitative imaging Performing and optimizing fluorescence-based