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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
Description The Research Center SHORES seeks to recruit a Postdoctoral Associate to work in the field of geotechnical engineering. Required Qualifications: The ideal candidate will hold a PhD in
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. Contribute to mentorship of students and lab group discussions. Minimum Qualifications: PhD in Chemical Engineering, Environmental Engineering, Materials Science, Mechanical Engineering, or a related field
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life-cycle assessment. The post-doctoral associate will be expected to lead research efforts and contribute to publications in reputable academic journals. Qualifications: A PhD in Civil and
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. Candidates with PhDs in Physics or Computer Science may also be considered if they willing to collaborate with mathematicians on these topics. For consideration, applicants need to submit a cover letter, a
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electrochemical separations. Work alongside researchers in materials science, chemical engineering, mechanical engineering, chemistry, and physics to develop innovative membrane technologies. Optimize membrane
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development of the group tasks and help in supervising PhD students. Applicants must have a PhD in experimental high energy physics or related field. Applicants need to submit a cover letter, curriculum vitae
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on the physical layer design of programmable metasurfaces enabled wireless communication systems. The candidate will investigate the role of programmable metasurfaces as reconfigurable holographic surfaces (RHSs
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of the advertised topics, as well as an excellent academic record. Candidates with PhDs in Physics or Computer Science may also be considered if they willing to collaborate with mathematicians on these topics
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will be under the supervision of CT&T Research Group Director Prof. Dr. Murat Uysal and is expected to carry out cutting-edge research on the physical layer design of wireless communication systems and
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workflows in complex organizational settings. Qualifications: Applicants must have a PhD in Computer Science or related field. Experience in one or more ML domains, such as deep learning, reinforcement