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Field
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by using explainable AI To develop generative AI techniques to design novel biologics for cancer Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or
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Supervised Machine Learning and Reinforcement Learning. The objective is to significantly enhance battery performance and longevity. While conventional methods rely on either physics-based models or high-level
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will a have a relevant PhD and medical degree alongside registration with the GMC at Specialist Registrar Garde or below. You will have a recent track record in histopathology and use of machine learning
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. The role will focus on developing machine learning and mathematical optimization solutions for electric vehicle fleet charging optimization under different constraints. Key Responsibilities: Formulate
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the appointment. The candidates should have a strong track record in at least one of the group’s research areas, preferably demonstrated by publications in high-impact venues. Experience with machine learning
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Econometrics Virtual power plants Power systems and/or power electronics Machine learning Renewable energy systems Advanced statistics Language requirement: Good oral and written communication skills in English
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thrombosis and lung injury in Sickle Cell Disease. The prospective candidate will have the opportunity to learn state-of-the-art techniques such as Multi-Photon-Excitation intravital microscopy of the lung and
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Engineering, etc.), expertise in cutting-edge AI and machine learning is essential; while structure prediction or materials chemistry experience would be advantageous, it is not a pre-requisite for the role
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active role in developing novel machine learning based systems and tools on the path towards clinical use and implementation of AI for the treatment and care of individuals also from minority populations
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, Safety and Health Regulations. • Assist in project resource requirements and managing student projects. Job Requirements: • Have a PhD Degree in Computer Engineering/Computer Science/Electrical Engineering