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http://www.ub.edu/caiac/solBeca?idConvocatoria=50433 Requirements Research FieldPharmacological sciencesEducation LevelPhD or equivalent Skills/Qualifications Degree in Pharmacy. PhD in pharmaceutical
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cancer cell growth and invasion, using a variety of 2D and 3D cancer models. Together, this project will determine whether specific cathepsins might represent novel targets to prevent tumour growth and
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of the following: 3D Printing, Computer-Aided Design, Organic Modeling, Device Development, Software Development, Immersive Technologies (VR, AR), Device Manufacturing. An advanced degree may
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is an in-person or hybrid role, we cannot accommodate a fully-remote candidate for this role. What You Will Be Doing Model and simulate: Build and mesh 3D model geometries Develop math models and
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Specialized areas: Deep Learning, Generative AI, Prompt Engineering, Conversational AI and Chatbots, Reinforcement Learning Applied domains: Machine Learning for Cybersecurity, AI for 3D Imaging, Recommender
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at the intersection of artificial intelligence and cultural heritage. The successful candidate will be involved in cutting-edge research and development in 3D computer vision and machine learning for the digital
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California State University, San Bernardino | San Bernardino, California | United States | 27 days ago
in the State of California. As of January 1, 2022 the https://calstate.policystat.com/policy/10899725/latest/ . Click or tap if you trust this link.' href='https://apptrkr.com/get_redirect.php?id
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Website: https://med.stanford.edu/stankovic-lab.html (link is external) https://hellerlab-stanford.net/ (link is external) How to Submit Application Materials: Please send the following materials in a
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Learning for Cybersecurity, AI for 3D Imaging, Recommender Systems, Quantum AI, Blockchain AI, AI for Autonomous Systems Foundational courses (for Connect pathway students): Python programming, Mathematical
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 3 months ago
modules leveraging deep learning for classical problems such as segmentation and 3D object tracking interfacing machine learning code and the robot using ROS2 contributing to the creation of datasets