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Field
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software vulnerabilities Research into novel methods of static and dynamic program analysis, including fuzzing and the use of AI methods for vulnerability detection Security analyses of real software systems
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Te Tari Pūhanga Pūmanawa Rorohiko | Computer Science and Software Engineering Located in Ōtautahi | Christchurch, Aotearoa | New Zealand Full-time 37.5 hours per week (1.0 FTE) Fixed term (1 years
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state-of-the-art verification techniques and tools for scientific software. The project is part of a program, sponsored by the U.S. Department of Energy and the U.S. National Science Foundation, named
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Computer Science, Software Engineering, Artificial Intelligence, or a related discipline. Strong research track record in software engineering, AI for code, or software security (e.g., publications in
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CSE applications through proxy applications representative of cross-cutting computation and communication motifs, and Software Development Kits (SDKs) seen as logical collections of well-integrated and
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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Science, Computer Engineering, or a related field. Strong background in smart contract security, blockchain systems, or software security. Experience in program analysis, formal methods, or vulnerability detection
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extraction). Provide technical guidance in project requirements, documentation, software solution design, architecture, and implementation across research-focused computational projects. Design, develop, train
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such as journal refereeing, participation in national planning exercises, or service on professional organization committees (e.g., APS DPF Coordinating Panel for Software and Computing). Application
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI