337 evolution "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "University of St" positions at Carnegie Mellon University
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(DoW) acquisition programs, program offices, or government-sponsored development efforts. Proven ability to lead, influence, or enable transformation, whether technical, organizational, process-oriented
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Associate II to work on an Agentic AI project for document understanding, especially in the legal domain. Core Responsibilities Working with databases and software development Machine learning and AI model
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flexible and encouraging environment where you can sharpen your skills, lead impactful projects, and take control of your career development. We are seeking a dynamic Senior Windows Software Engineer to lead
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creating and leading innovative business ventures. They will have demonstrated knowledge of and experience in early-stage development and funding of companies, a history of building and maintaining critical
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understanding of placental development through the integration of computational modeling and clinical imaging data within the Biomedical Flows Simulation and Multiscale Modeling (BioSiMM) Lab. Core
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announcement requirements, budget development, preparation of internal and external proposal forms, and use of electronic proposal submission modules. The incumbent will have daily interaction with faculty
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Associate to assist with statistical modeling of single-cell multiome data, development of algorithms to link enhancers with their cis-regulatory gene targets, simulation studies and real-data benchmarking
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The Mission: In modern warfare, the speed of relevance is determined by the speed of software. The Software Engineering Institute (SEI) is at the forefront of this evolution. Our team is
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-Level Technical Roles IT support/help desk, data entry, lab technician roles, or junior web development. What We’re Looking For At Carnegie Mellon, we value adaptability, excellence, and passion. We’re
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods