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limitations —driven to explore solutions that go beyond what verification alone can achieve. This PhD project focuses on developing analysis and program repair techniques that enhance software interoperability
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training and professional development opportunities, holiday leave, accommodation in NUSTPB residences, banking facilities, access to research infrastructure, and software for remote working. Eligibility
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models, real-time telemetry, and AI-enhanced analytics, the research aims to enable continuous simulation and verification across the entire ECU lifecycle—from early model-in-the-loop design to deployment
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from software error discovery to mitigation based on modern active learning. Job Description You will research the state-of-the-art in AI and apply it to real-world software problems at our industrial
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Find2Fix will engineer the first open-source tool for the entire process from software error discovery to mitigation based on modern active learning. Job Description You will research the state
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new paradigm in the validation of autonomous driving software, focusing on the intersection of Large Language Models (LLMs) and Autonomy 2.0 / End-to-End (E2E) approaches. While E2E models promise
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techniques with open-source autonomous driving software (for sim- ulation and testing) Applicants should fulfil the following requirements: a master’s degree in engineering sciences (preferably in computing
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advantages. We will provide the necessary hardware and software for the real-time control of the machine, but the candidate will be responsible for developing and implementing the control algorithms. A working
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component modeling and testing. Knowledge or classwork related to energy systems with design and computational model analysis using engineering software will be necessary. Demonstrated research capability and
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team of engineers, analysts, and software developers. GAC works to develop and apply state-of-the-art energy system modeling techniques, software, and simulations for breakthrough engineering and techno