Research Engineer, Semiconductor, Iaic

Job Summary We are seeking a highly motivated Research Engineer to support the development of AI-driven modelling and simulation technologies for advanced photonics and semiconductor applications. The successful candidate will work at the intersection of physics-based simulation, artificial intelligence, inverse design, and design-for-manufacturing. The research scope will include advanced photonics, power electronics, and lithography–etch optical proximity correction. The candidate will contribute to translating emerging research concepts into practical device designs and manufacturing-ready solutions under Singapore’s semiconductor and photonics research initiatives, including NSTIC and IAIC programmes within A*STAR. Key Responsibilities Develop physics-guided AI and machine-learning models for photonic-device and semiconductor-process modelling. Perform electromagnetic, optical, lithography, etch, and semiconductor-device simulations using tools such as FDTD, FEM, RCWA, TCAD, and lithography simulators. Develop AI-assisted inverse-design and optimization workflows for photonic structures under optical-performance and fabrication constraints. Support lithography–etch OPC development, including layout processing, lithography prediction, etch-bias modelling, SEM-data analysis, pattern correction, and post-fabrication validation. Collaborate with researchers, process engineers, fabrication teams, and external partners to translate research outcomes into practical demonstrators and manufacturing solutions. Prepare technical reports, presentations, software documentation, and research publications. Qualifications Bachelor’s or Master’s degree in Electrical or Electronic Engineering, Physics, Photonics, Materials Science, Mechanical Engineering, Computer Engineering, or a related discipline. Candidates with a relevant PhD may also be considered, subject to experience and position requirements. Fresh graduates with strong project experience are welcome to apply. Technical Requirements Good understanding of electromagnetics, optics, photonics, semiconductor physics, or semiconductor manufacturing processes. Experience with one or more numerical simulation methods, such as FDTD, FEM, RCWA, BPM, Fourier optics, TCAD, or lithography simulation. Proficiency in Python for scientific computing, data analysis, and simulation automation. Basic knowledge of machine learning and optimization methods. Preferred Skills Experience with simulation platforms such as Ansys Lumerical, COMSOL, MEEP, Zemax OpticStudio, Sentaurus TCAD, Prolith, or equivalent tools. Familiarity with AI frameworks such as PyTorch or JAX. Knowledge of physics-informed neural networks, surrogate modelling, Bayesian optimization, reinforcement learning, topology optimization, adjoint optimization, or generative design. Understanding of design-for-manufacturing principles for wafer-scale nanophotonics and semiconductor fabrication. Experience with Linux, version control, high-performance computing, or parallel simulation workflows would be advantageous.