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and Research: The professor will develop research activities in several aspects of computer science, including but not limited to algorithms, databases, cloud computing, machine learning, operating
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Assist Prof in Next-Generation Approaches of Remote Sensing for Applications to digital soil mapping
spectroscopy for multi-scale soil fertility mapping and assessment, Develop hybrid approaches combining radiative transfer model and Next-Generation Approaches of Remote Sensing such as machine learning (ML
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Assist. Prof in Next-Generation Approaches of Remote Sensing for Applications to Digital Agriculture
crop growth and yield, Develop hybrid approaches combining radiative transfer model and Next-Generation Approaches of Remote Sensing such as machine learning (ML) regression algorithms for timely and
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& Catalysis 3. Energy-saving Materials and Technologies 4. Sustainable Exploitation & Utilization of Resources 5. Cycling and Purification of Key Elements 6. Carbon Capture, Utilization, and Storage 7. Machine
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at the scientist/professor level depending on the CV and past experience of the successful candidate. The candidate is expected to combine machine learning and geosciences to develop innovative research related
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in vitro. Clive Svendsen, PhD, has significant experience in studying these diseases over the last twenty years and is merging his experience with the use of leading-edge technologies, such as
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seven computer scientists. Candidates must have a PhD in Biostatistics or Statistics and a record of peer-reviewed publications showing evidence of (for Instructor and Assistant Member, a potential of
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on rapid development of editing strategies for rare patient-specific mutations. Optimize lead protein candidates by structure-guided design and high-throughput screening. Apply new machine learning
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to regulatory networks and circuit design, metabolic engineering, molecular pharming, or RNA biology and applications. The candidate will demonstrate research excellence, hold a PhD or equivalent, and have
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structure and dynamics, gene regulatory networks, functional genomics, systems biology, multi-scale modeling, synthetic biology and novel machine learning/deep learning based approaches in computational