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Field
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Status: Nonexempt Work Schedule: Flexible Summary The intern will receive training on machine learning algorithms, implementing them, and fitting them on the datasets in our cluster computers. Overall
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. Knowledge or experience of Robot Operating System (ROS), tools for training and using deep learning algorithms and in image processing and computer vision algorithms and solutions using open-source software
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need. Apply AI and machine learning algorithms to software engineering projects in the researcher’s specific domain. Application of Domain Expertise Initiate and maintain open collaboration with
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on Wednesdays and Fridays 11:35-12:55 and labs Mondays 15:35-17:25. This course includes an Introduction to problem-solving methods and algorithm development. Emphasis is on designing, coding, debugging, and
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will be able to teach one of the undergraduate courses related to AI/ML, programming languages, data structures and algorithms, operating systems, network security, visualization, and human-computer
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data and machine learning processing pipelines. It will also focus on developing AI algorithms for semantically enriching data assets with domain knowledge, which feed into building knowledge graphs
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Responsibilities: Develop novel quantum reinforcement learning (QRL) algorithms using variational quantum circuits (VQCs), focusing on the multi-agent setting. Design and implement efficient credit assignment
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algorithms and data structures. Experience with AI frameworks and libraries (e.g., TensorFlow, PyTorch). Ability to develop and implement AI models for business applications. Knowledge of cloud computing
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science topics, including practical software development skills. Expertise in teaching mathematical subjects related to computer science such as discrete structures, analysis of algorithms, artificial intelligence
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This position is ideally suited to someone wishing to transition from a post-doctorate career in academia to commercial software and algorithm development. You are not expected to be an AI expert