20 machine-learning-"https:" "https:" "https:" positions at Pennsylvania State University in United States
Sort by
Refine Your Search
-
his collaborators, Yan Li in the Electrical Engineering department, and Daning Huang in the Aerospace Engineering department in the area of Scientific Machine Learning. The project is to develop
-
systems, devices (including fabrication) and sensors, robotics and automation, artificial intelligence and machine learning, advanced electronics, and communications. Our faculty are particularly encouraged
-
federated learning, AI security and privacy, quantum machine learning (QML), robotics, and/or AI-driven discovery in science and engineering (e.g., genomics, bioinformatics, drug discovery, infectious disease
-
artificial intelligence, machine learning, deep learning, natural language processing, and generative AI, as well as emerging areas such as agentic AI systems, low-code/no-code AI platforms, and responsible AI
-
of scholars and students at the forefront of computer vision research and material studies with longstanding research strengths in architectural history. The Center for Virtual and Material Studies (https
-
or Full Professor position in Computational Mathematics. The search is open to any area in Numerical Analysis, Foundations of Machine Learning, Data Driven Methods, Quantum Computing, or other areas within
-
expected to teach undergraduate courses and guide senior design projects in the area(s) of engineering and design, system dynamics, measurements and instrumentation, and fundamental computer programming
-
candidates who can build a strong methodological research base in areas of Operations Research, including optimization, stochastics, simulation, machine learning and artificial intelligence. Applicants at all
-
Learning Design and Technology, Human-Computer Interaction, Media Arts or Digital Media, Emerging Technologies, or a related field will be considered a plus. MINIMUM EDUCATION, WORK EXPERIENCE & REQUIRED
-
models, artificial intelligence, Bayesian models, data visualization, dynamic causal models, dynamic systems models, item response theory, large language models, machine learning, mixture models