568 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"Bournemouth-University" positions at Nature Careers
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peripherals). Experience supporting business teams around IT needs. Prefer experience with Windows, Apple, and Linux. Licensure, Registration and/or Certification Required by SJCRH Only: Certification in A
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for early-stage cancer using statistics and/or machine learning (including deep learning where appropriate). You will join a vibrant and growing research group of 12 scientists (six postdoctoral researchers
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of competitive research proposals. You should have experience in the following areas: Applied Machine Learning for Autonomous Systems: Experience developing and deploying ML models for perception, prediction
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Vineyard’s second area of focus (above) and will be central to the Department’s strategic focus on harnessing data science, machine learning, and AI to transform cancer research. The Division Chief will lead
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this but have hitherto struggled with tackling such challenging systems. With the emergence of machine learning methods in the physical sciences, things are rapidly changing. This project is part of a
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healthcare data. * A team player who thrives as a member of a highly functional cross-disciplinary team Preferred Elements * B.S, M.S., and/or PhD in Computer Science, Biomedical Informatics, Machine Learning
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with Artificial Intelligence and deep learning concepts for robotics computer vision, tactile sensing, reinforcement learning Experience with robotic simulation tools e.g., ROS, Gazebo, Mujoco, IsaacSim
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Software Engineer - Image Quantification and Artificial Intelligence (IQAI), Department of Radiology
space where you define the technical roadmap for computer vision and medical imaging breakthroughs. We are looking for a software engineer who is dissatisfied with the status quo and possesses
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service, or similar circumstances, as well as clinical practice or other forms of appointment / assignment relevant to the subject area. Project 1: Growth dynamics of the world’s longest-lived algae
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technologies (fiber-optic sensors, DIC), and computer science (machine learning tools) in collaboration with de department of Physics. The aim of the BriCE project is to develop a novel bridge monitoring