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Field
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Postdoctoral Research Associate in Sum-Frequency Generation Microscopy of Biomolecular Self-Assembly
the institute focusses on the structure and dynamics of elementary processes in solids and at surfaces. Within this broader research theme, the Nonlinear Chemical Imaging (NCI) group of Dr. Alexander Fellows
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of optics, imaging systems, digital holography, speckle metrology, Matlab and simulations, signal processing, the Fourier transform, machine learning, and classifiers such as SVM. Meriting qualifications
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on unravelling the middle to late Proterozoic marine water chemistry and implications of this for the evolving earth system. This work is part of a larger ambitious research program to investigate
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Previous Job Job Title Post-Doctoral Associate - Electrical and Computer Engineering Next Job Apply for Job Job ID 369523 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular
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vision, controls, cyber-physical systems and their security, hardware security, and machine learning and their security. The work will include algorithm design, prototype implementation (e.g., in Matlab
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30 Aug 2025 Job Information Organisation/Company CNRS Department Laboratory of Pathogens and Host Immunity Research Field Biological sciences Medical sciences Pharmacological sciences Researcher
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the First Team programme of the Foundation for Polish Science co-financed by the European Union under the European Funds for Smart Economy 2021-2027 (FENG). The aim of the project is to establish conditions
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imaging is also required. However, experience with bioinformatics or computational tools for biology is highly recommended but not required. This position provides an opportunity to lead and run experiments
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skills; and ability to understand and communicate in English to sufficiently perform the job duties. Must be computer literate with proficiency and working knowledge of database and reporting tools such as
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of mouse behavioral paradigms is required. Extensive computer programming experience in python or Matlab and the ability to deal with large, complex datasets are required. Experience with preparation and