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of the developed algorithms Overseeing project budget and coordinating the procurement and maintenance of equipment Providing mentorship and academic guidance to students Preparing and compiling reports pertaining
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: Writing, debugging, optimizing and testing of source code with an emphasis on audio applications. Maintenance and improvement of existing audio algorithm code base including noise reduction, acoustic echo
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Responsibilities: Identify the weakness of existing watermarking and adversarial protection methods Develop new deep learning algorithms or improve existing algorithms to address the weaknesses. Prepare codes and
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, control algorithms, optimization techniques, and optimal energy management algorithm development for the optimal operation of the system and applications. • Strong knowledge of power electronics, wide
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academic experience in one or more of the following, or closely related, areas: AI Ethics and Responsible AI Software Engineering Programming Fundamentals Algorithms and Problem Solving Software Design and
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environments. Develop and refine advanced optimization algorithms for the Energy Management System (EMS), including energy dispatch, energy storage control, load scheduling, and market participation strategies
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: Python, R, Java, C++, C#.Net, SQL. Proficiency in using Business Intelligence tools (e.g. Power BI, Tableau or Qlik Sense) Experience in applying machine learning techniques and designing algorithms
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, development of algorithms, publications and/or patents. Strong algorithm development and programming skills in MATLAB/Pyton and C++ Working knowledge of state of the art machine learning techniques Familiarity
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and optimization algorithms Optimization of indoor farms Provide regular project updates to principal investigator and funding agency Report writing/presentation Job Requirements: Diploma or Bachelor’s
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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