Experience and skills in scientific programming (e.g. Python or C/C++) and data analysis, including experience with UNIX/Linux operating systems and command-line environments (e.g. Bash). Experience in machine learning & deep learning, database, and good understanding of high-performance computing hardware is a plus.
A track record of publishing papers in decent scientific journals and excellent writing & presentation skills.
Able to collaborate with experimentalist and work with other team members.
We are seeking a highly motivated and talented Research Fellow to join our team in the development of rechargeable batteries using computational design. As part of this project, you will play a key role in designing composites materials using inorganic solid electrolytes using computational modelling and machine learning.
• Ph.D. in Materials Science, Chemistry, Physics, or a related field.• A deep understanding of solid-state physics/chemistry and general physical chemistry. Knowledge of rechargeable battery and electrochemistry is a plus. Experience in computational modelling of inorganic solid electrolyte or other energy materials is desired.• Well-equipped with different tools of materials modelling. Prior experience of computational modelling of functional materials using DFT (VASP) and molecular dynamics with machine learning force fields is desired.• Experience and skills in scientific programming (e.g. Python or C/C++) and data analysis, including experience with UNIX/Linux operating systems and command-line environments (e.g. Bash). Experience in machine learning & deep learning, database, and good understanding of high-performance computing hardware is a plus.• A track record of publishing papers in decent scientific journals and excellent writing & presentation skills.• Able to collaborate with experimentalist and work with other team members.
Fabricate and characterize 2D amorphous carbon-based devices and test structures.
Evaluate dielectric, structural, mechanical, electrical, and diffusion-barrier properties of MAC films.
Develop application use cases for 2D amorphous carbon films in ultralow-k dielectrics, interconnect integration, diffusion barriers, magnetic media, and protective coatings.
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The successful candidate will work with Professor Barbaros Oezyilmaz and Dr Toh Chee Tat on applications of 2D Amorphous Carbon under the Central Gap Fund grant on commercializing a breakthrough Ultralow-K (ULK) Monolayer Amorphous Carbon (MAC) dielectric technology. Having successfully validated the core materials physics at the lab scale, we are now solving critical reactor scaling challenges to transition our UV-CVD prototype into a scalable 200mm/300mm commercial alpha tool. This technology solves the critical interconnect RC-delay bottleneck in sub-3nm advanced CMOS nodes and has already secured strong evaluation traction from top-tier global semiconductor and equipment manufacturers.
The main responsibilities of the position include:• The project aims to translate ultralow-k monolayer amorphous carbon dielectric technology from lab-scale validation toward a scalable UV-CVD platform compatible with 200 mm / 300 mm wafer processing. The successful candidate will work on the development, characterization, and commercialization of 2D amorphous carbon materials for advanced semiconductor and related industrial applications.The candidate will:• Develop and optimize wafer-scale UV-CVD growth processes for 2D amorphous carbon films. • Address reactor-scaling challenges required to transition the current prototype toward a commercial alpha-tool platform. • Fabricate and characterize 2D amorphous carbon-based devices and test structures. • Evaluate dielectric, structural, mechanical, electrical, and diffusion-barrier properties of MAC films. • Develop application use cases for 2D amorphous carbon films in ultralow-k dielectrics, interconnect integration, diffusion barriers, magnetic media, and protective coatings. • Analyse industry bottlenecks and define how MAC materials and processes can address urgent technology challenges. • Work with industrial partners to establish evaluation protocols, performance targets, and joint development opportunities. • Contribute to high-impact publications, patent filings, invention disclosures, and translational grant deliverables. • Identify suitable industrial collaborators and support licensing, joint development funding, and commercialization activities. • Mentor PhD, Master’s, and undergraduate students working on related research tasks.
Qualifications / Discipline:Candidates should hold a PhD in Physics, Materials Science, Nanoscience and Nanotechnology, Electrical Engineering, Chemical Engineering, or a closely related discipline.Skills:The ideal candidate should demonstrate:1. Strong spectroscopy expertise, including experience with techniques such as photoluminescence, Raman spectroscopy, and X-ray photoelectron spectroscopy. 2. Experience with synthesized or naturally derived 2D materials, including exfoliation, stacking, transfer, synthesis, or device integration. 3. A strong understanding of chemical vapour deposition processes and the growth of low-dimensional materials. 4. An established network for collaboration in materials characterization, device fabrication, and application development. 5. Independence, initiative, and strong time-management, planning, and organizational capabilities. 6. Ability to perform detailed risk assessments, prepare experimental protocols, troubleshoot complex technical issues, and make sound technical, administrative, and procedural decisions. 7. Excellent spoken and written English communication skills. Experience:Candidates should have at least 5–8 years of laboratory research experience, preferably with a focus on nanomaterials, low-dimensional materials, or technology validation for advanced materials applications.Experience in research project management, coordination of collaborative projects, or supervision of junior researchers is strongly encouraged.
Perform research in operando imaging guided materials design for single-entity insights
The successful candidate should possess the following:• A PhD in Materials Science, Chemical Engineering, Chemistry, Physics, or related fields• Highly motivated, committed, and capable of working independently as well as collaboratively• Strong publication record in peer-reviewed journals• Good communication skills in English (both written and oral)
Prior experiences with the following will be a plus:
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Perform research in neuromorphic computing devices.
The successful candidate should possess the following:• A PhD in Materials Science, Chemical Engineering, Chemistry, Physics, or related fields• Highly motivated, committed, and capable of working independently as well as collaboratively• Strong publication record in peer-reviewed journals• Good communication skills in English (both written and oral)• Prior experiences with the following will be a plus• Optical instrumentation, single-molecule/ super-resolution microscopy, magnetic/optical tweezers, ultrafast spectroscopy, or other in-situ operando imaging tools• Machine learning for materials discovery or quantitative image analysis, DFT calculations for catalyst design, experiences with MATLAB / Python / AutoCAD / COMSOL• Organic synthesis, polymer chemistry, synthesis of inorganic nanomaterials, micro/nano-fabrications, genetic engineering of microorganisms• Techno-economic analysis of sustainability technologies
For postdoctoral fellows, compensation and benefits package will be internationally competitive (including annual base salary, performance-based bonus, medical insurance and vacation leave), and will be commensurate with experiences and qualifications.
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Excellent problem-solving skills and ability to work independently and collaboratively.
Strong written and oral communication skills.
Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.
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