Scientist/Senior Scientist (DMD Division/CPPS Group), SIMTech

Agency for Science, Technology and Research
Singapore
3 months ago
Applications closed

Related Jobs

View all jobs

Higher/Senior Scientist in Quantum Computing and Machine Learning

Senior Data Scientist

Data Scientist/ Senior Data Scientist P Znamenskiy lab

Data Science & Machine Learning - Senior Associate - Asset Management

Data Scientist, United Kingdom - BCG X

Data Scientist, United Kingdom - BCG X

Job Description:

The CPPS group is seeking a highly motivated scientist or senior scientist to lead in the development of AI technologies to deliver impactful and innovative digital technologies for predictive/prescriptive analytics and decision support. He/she will be expected to define growth opportunities and new ways to engage industry to advance AI for manufacturing, and look after a team of scientists and engineers to translate problems faced by industry into opportunities to develop and deploy deep tech in AI. The key roles & responsibilities include, but are not limited to the following:

  • Develop AI models to enhance and automate decision making and enable predictive/prescriptive analytics
  • Define opportunities to push frontiers of AI research in manufacturing
  • Formulate research direction and proposals for competitive funding to advance AI in manufacturing
  • Engagement of companies to understand their challenges and translate to research collaborations in AI
  • Work with a team of scientist and engineers to execute deliverables for industry projects
  • Contribute to research and development in Cyber-Physical Production System technologies
  • Develop research proposals to secure competitive funding
  • Lead technology development, live production environment testbedding and technology transfer of robust algorithms to industry
  • Understand autonomous manufacturing domain and provide innovative solutions to industry problems in this area
  • Familiarity with Industry 4.0 standards and concepts is an advantage

Job Requirement:

  • PhD in Computer Science, Data Science or Mechanical/Industrial/Electrical Engineering
    7 years' experience in developing and deploying machine learning and data analytics (for Senior Scientist)
  • Strong leadership skills
  • Programming/coding skills in developing AI and data analytics
  • Skills in data modelling, machine learning, signal processing
  • Good track record of publications
  • Excellent verbal and written communication skills
  • Quality focused and customer-centric
  • Can-do attitude and able to work with different needs of various stakeholders
  • Proactive team player and technically motivated to solve problems innovatively

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.