453 computational-physics-"https:"-"https:"-"https:"-"https:"-"Caltech" positions at Carnegie Mellon University
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machine learning methods. Technical Experimentation: You will experiment with modern and emerging machine learning frameworks, methods, and algorithms in application domains that include computer vision
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of International Education, EM Marketing & Communications and Enrollment Systems. Collaborate with strategic campus partners such as Institutional Effectiveness & Planning, Computing Services
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. This encompasses the full pipeline of organ biofabrication—from computational design and advanced bioprinting to bioreactor maturation and in vivo validation. The LIVE project represents a bold and collaborative
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national resource in software engineering and computer security. SEI works closely with academia, defense and government organizations, and industry to continually improve software-intensive systems. Our
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challenges. Requirements: Enrolled in a degree granting program. Willingness to travel to various locations to support the SEI’s overall mission. This includes within the SEI and CMU community. You will be
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generative AI and large language models, computer vision, multimodal AI, agentic AI, and assurance of AI systems. Additionally, we craft metrics and experimental designs for large-scale cybersecurity research
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eligible employees enjoy a wide array of benefits including comprehensive medical, prescription, dental, and vision insurance as well as a generous retirement savings program with employer contributions
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to support and help guide graduate admissions for the Master of Science in Software Management program. This advanced position is ideal for someone with deep experience in holistic evaluation, strong
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, or presentation; writes technical reports. May build and validate quantitative models. Identifies problems and obstacles to progress; develops strategies to solve problems. May program software in support of job
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for the Pitkow Lab. Core Responsibilities Include: Develop computational methods for inference and control that improve the reliable and efficient operation of autonomous agents in complex, uncertain environments