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Field
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, Algorithmic Foundations of Optimization, Data Mining, Machine/Artificial Intelligence A combination of education and relevant experience from which comparable knowledge is demonstrated may be considered
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use of data and algorithms. Excellent written and verbal communication skills and ability to communicate effectively with a variety of different stakeholders, e.g., academics, business executives
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on Geospatial Analytics in Geomatics, including – but not limited to – advanced Artificial Intelligence/Machine Learning (AI/ML) techniques and scaleable application architectures and algorithms for geospatial
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with rare, resistant, or genomically un-targetable cancers. Responsibilities Design and evaluate algorithms for treatment and response matching using integrated clinical and molecular datasets. Develop
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to thrive in a highly cross-functional environment. They will be responsible for the development of algorithms for early, blood-based detection tests for cancer. They will build on a foundation of ML/DL and
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the future of technology. Essential Duties and Responsibilities Design, simulate, and implement advanced control algorithms (e.g., PID, adaptive, model predictive control. Etc.) for biomedical devices and
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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strong commitment to teaching, academic research, and service. Preferred Qualifications Research that focuses on artificial intelligence or database systems and teaching interests in algorithmic
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teaching, academic research, and service. Preferred Qualifications Research that focuses on artificial intelligence or database systems and whose teaching interest relates to algorithmic programming and
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: Develop electromagnetic transient models for bulk power systems, power electronics-based resouces (e.g. HVdc, solar PV inverters), synchronous generators, loads, etc. Develop simulation algorithms