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high-quality research publications and contribute to report and technological disclosures writing. Job Requirements: PhD degree in the areas of Optical Engineering and/or Photonics devices and System
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Performing CO2 adsorption and mixed-gas separation performances Job Requirements: PhD from a reputable university in the field of chemistry, chemical engineering, materials science or other related disciplines
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papers Contributing to quarterly and annual report writing and presenting Job Requirements: PhD degree in Artificial Intelligence, Computer Science, Software Engineering Strong background and research
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and technological disclosures writing. Job Requirements: PhD in Computer science, Computer engineering, or related field. Experience in privacy-preserving techniques’ research and implementation. Strong
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of research. Job Requirements: Preferably PhD in Computer Science or equivalent. Independent, highly analytical, proactive and a team player Excellent teamwork and verbal, written communication skills In-depth
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predictions for the spatiotemporal interaction between free electrons, photons and nanomaterials Publish high quality papers Requirements PhD in Engineering, Physics or related field Knowledge in classical
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organization, safety, and equipment maintenance. Job Requirements: PhD in Chemistry, Materials Science, Chemical Engineering, or a related field Research experience in heterogeneous catalysis, with knowledge in
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products. Apply the knowledge to correlate results / system operation. Set-up and monitor the performance of systems Job Requirements: PhD degree in a relevant Science or Engineering field Strong analytical
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writing/presentation Job Requirements PhD degree in an engineering field related to this project Experience in dynamic modeling, machine learning and optimization & controls Having basic knowledge in carbon
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updates to principal investigator and funding agency Report writing/presentation Job Requirements PhD degree in an engineering field related to this project Experience in dynamic modeling, machine learning