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for submission to premier venues (CVPR, ICCV, ECCV, NeurIPS, ICLR). Convert research prototypes into scalable, deployable software systems or proof-of-concept demos. Design, code, and optimize robust deep learning
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or experimental process data is advantageous; coating or functional-materials knowledge is a plus. Proven research capability through publications, conference papers, patents, software or comparable outputs
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spectrum-sharing techniques using software-defined radio and wireless system emulation across technologies including 5G/6G, Wi-Fi and satellite. Apply AI/ML and data-driven approaches to spectrum management
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focuses on software development using LLM-generated code. It will evaluate students’ ability to evaluate the correctness and computational efficiency of LLM-generated code, including whether more efficient
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into products. This toolkit will be composed of an integrated suite of software and experimental tools and will be informed by the collection of data en route to the development of advanced 3D printed products
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. Collaborate closely with AI, machine learning, and software engineering teams to translate operational requirements into deployable human-centred solutions. Engage with operational stakeholders, including air
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machine learning methods • Proficiency in transport planning software such as EMME or PTV Visum. • Programming expertise in at least one language, e.g., Python, Java, or C++. • Strong written and
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/ROS 2, Linux, Git, and robotic software development. • Hands-on experience integrating robotic software with UAV hardware, cameras, embedded computing platforms (e.g., NVIDIA Jetson), and
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operating advanced characterization (TEM, SEM, XRD, XPS, etc.); Good publication record (at least two first-author papers in international journals); Experience on the LPBF process monitoring and software
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holder will be responsible for the design, development, optimisation and validation of advanced optical instrumentation and associated software platforms for both in vitro and in vivo applications