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property prediction, modern artificial intelligence methods, molecular dynamics, and interdisciplinary research, this is your chance to be part of an exciting journey at the forefront of science and
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scientifically contributing to projects in Robotic Manipulation for Space Robotics. The candidate will carry a leading role in this area and support PhD candidates in their thesis research. The candidate will work
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have or be close to finishing a PhD in bioinformatics, artificial intelligence, biophysics, or computational biology. The ideal candidate will have demonstrated experience in developing and applying
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grant applications Experimental work will include molecular engineering, protein characterization, and cellular functional validation in engineered T cells. We are looking for a candidate who: Holds a PhD
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Classification Title: RES AST SCTST Classification Minimum Requirements: PhD in Mechanical Engineering, Material Science, Chemical engineering, or a closely related field e.g., nanoscale transport
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Experience Appropriate PhD in a related field. Preferred Qualifications Experience with machine learning and deep neural network techniques. Experience with wearable and sensors placed in the environment
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contribute to ongoing research projects with Artificial Intelligence (AI) focus related to the Center for Applied Research on Work (CAROW). Responsibilities include: the utilization of direct data and
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contributing to computational model development The position is primarily computational and AI-driven, with close interdisciplinary collaboration. Qualifications We are looking for a candidate who: Holds a PhD
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Learning Through Research (CATLR), and the Office of Faculty Development (ADVANCE). We welcome applicants with recently-awarded PhD, EdD, or related doctoral degrees (2023 or later) from the humanities and
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
based on experimental and computational data. Establish predictive models based on artificial intelligence methods. Utilize the developed models to design and optimize the properties of materials. Conduct