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Postdoctoral Researcher in Multimodal Machine Learning for Precision Cancer Medicine The Machine Learning in Biomedicine (MLBioMed) research group at the Institute for Molecular Medicine Finland
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Grant, focusing on the development of novel deep learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted
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biogeography, with a strong emphasis on computational data analysis. Alternatively, the candidate may hold a master’s degree in statistics, machine learning or related field, accompanied by prior experience
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at Aalto University (https://into.aalto.fi/display/endoctoralsci/How+to+apply#Howtoapply-Eli… ) a Master’s degree in Artificial Intelligence, Machine Learning, Computer Science, Cognitive Science
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settings. Using advanced compressed sensing techniques and machine learning methods, PulseZTE will make it possible to image neural activations and vascular pulsations simultaneously. It will also enable
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, communicate proficiently, and have collaboration skills Knowledge of 3D computer vision, tomography reconstruction, electron microscopy, and MRI is a plus. Your benefits You will have access to the university’s
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to teaching or supervision duties. Requirements The successful applicant should have a doctoral degree in statistics, mathematics, machine learning, or other relevant field, and experience in developing and
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, calibration, and the development of analysis tools and software. Our key focus areas are the physics of jets, top quarks, and EWSB, including the development of novel machine-learning methods for high-energy
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analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and database systems. The department has extensive
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at the University of Helsinki. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms