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machine learning, computer vision, human-computer interaction, or similar relevant areas. Experience in research or development on bias, interpretability, and/or privacy in machine learning/AI is necessary
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to demonstrate effective and efficient multi-tasking and maintain accurate and up-to-date records. In addition, the applicants should have a high level of proficiency with computer software related to laboratory
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superconducting quantum processor at Aalto University’s Quantum Coputing and Devices (QCD) group at the Department of Applied Physics. In this position you have a chance to make history by demonstrating some of the
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candidate will help to support the team to formally document algorithms within a quality management system. EpiNav™ provides state-of-the-art computer-assisted support for the planning of stereotactic
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becomes essential. This project will focus on building a comprehensive digital twin of a future quantum computer to investigate how classical subsystems scale and interact, and how this scaling impacts
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the risks. You will have: a PhD in one of the relevant STEM disciplines, such as mathematics, statistics, computer sciences, theoretical food, ecological or physical sciences, etc. skills in mathematical
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and leading a programme of numerical simulations relating to all aspects of our research on P-MoPAs; using particle-in-cell computer codes hosted on local and national high-performance computing
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and statistical modelling, statistical image analysis and computer vision, chemometrics, biophysics, bioengineering. Preference will be given to candidates with a demonstrated experience in applying
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Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research Associate: A PhD (or
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or military collaborators. You are expected to have strong mathematical and programming skills, knowledge of computer vision and data mining tools, and be able to work on group software projects using modern