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required: Experience with developing bioinformatic tools (webserver/package) Experience with machine learning Strong background in molecular/cellular biology Experience with analyzing large and complex
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programming skills Experience with developing machine learning models, probabilistic modeling or other bioinformatic tools Any of the following features are highly desirable, but not strictly required
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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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Postdoc in CRISPR Meta-Analytics and AI for Therapeutic Target Discovery and Priotisation (OT Grant)
solutions. Situated in the Computational Biology Research Centre of HT, the Iorio Lab operates at the intersection of biology, machine learning, statistics, and information theory. Our goal is to comprehend
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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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of the second year after a trainee joins the team. Job Duties Designs and implements novel computational algorithms for data analysis, feature extraction, and predictive modeling. Applies machine learning
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in the application of machine learning methods, mixed models, clustering techniques, sinusoidal regression, and regression splines. Medical background and knowledge of biochemical processes is a plus