DSO National Laboratories (DSO) is Singapore's largest defence research and development (R&D) organisation, with the critical mission to develop technological solutions to sharpen the cutting edge of Singapore's national security. At DSO, you will develop more than just a career. This is where you will make a real impact and shape the future of defence across the spectrum of air, land, sea, space and cyberspace.

The Emerging Systems Division focuses research and development on a broad spectrum of capabilities that are critical to the Singapore Armed Forces (SAF) defence systems. These include antenna design and electromagnetics, as well as next-wave technologies in the areas of lasers and advanced materials.

People are DSO’s greatest asset. You will get to realise your career aspirations and develop your own niche either as a deep technical expert or a leader in the team. With frequent career dialogues and a robust training and development framework, we will provide you with the necessary development tools for you to reach your potential. You will also be recognised and rewarded through competitive remuneration packages and scholarship opportunities.

Artificial Intelligence R&D Engineer (Materials)

In this role, you will:

• Leverage cutting-edge artificial intelligence (AI) and machine learning techniques to accelerate the development of advanced materials with functional and/or smart properties, and optimize their properties for diverse applications
• Support technology developmental projects by exploring concepts on AI for materials
• Design and execute data-driven workflows, including executing data collection using physics-based M&S tools and exploring various state-of-the-art AI techniques such as generative methods and various optimization techniques towards materials design and discovery
• Perform validation on the novel materials using M&S tools and potentially in an in-lab environment

Requirements

• PhD / Masters / Bachelor’s Degree in Computer Science / Material Science / Applied Physics
• Possess knowledge in machine learning and AI
• Self-driven, able to exhibit analytical thinking to address and solve unstructured problems
• Strong proficiency in coding especially in Python
• Prior experience with deep learning frameworks (e.g. PyTorch, Tensorflow or JAX) or popular ML libraries would be advantageous
• Prior R&D experience in applying AI for science and engineering applications would be advantageous