Research Scientist , SCIS
Research Scientist , SCIS
Singapore Management University3-5 Years
- Posted 6 hours ago
- Be among the first 10 applicants
Job Description
Responsibilities
- This position is for School of Computing and Information Systems (SCIS).
- Design scenario modeling methods for ADS testing.
- Design algorithms for critical scenarios generation;
- Develop methods for failure analysis and root cause analysis of critical scenarios;
- Develop methods to mitigate failures and improve ADS safety;
- Investigate robust motion planning for ADSs that can tolerate module failures in ADSs.
- Write research papers.
- Other duties as assigned.
- Minimum PhD degree in Computer Science, Information Technology, Information Systems or closely related disciplines with particular focus on Computer Science.
- Minimum 3 years of relevant research experience in AI security, Autonomous Driving System testing.
- High-quality publications in top-tier software engineering/security/AI journals or conferences.
- Proficiency in programming software/languages such as Python and Pytorch will be positively considered/ is required.
- Proven track record and professional experience in ADS testing, AI testing and software anlysis.
- Demonstrated experience and know-how on testing and repair AI systems, particular on ADS systems.
- Excellent working knowledge of machine learning, trustworthy AI and software testing.
- Technical skills in ADS testing, software testing and bug fixes.
- Ability to break down complex problems and design effective solutions.
- Innovating new approaches and thinking outside the box.
- Applicants with research publications in AI security, software engineering and cybersecurity area will be advantageous.
- Ability to work cooperatively as part of a small, agile academic research team is essential.
- Self-motivated individual who can work independently and collaboratively with team members.
More Info
Key Skills
Autonomous Driving System testing
AI security
trustworthy AI
bug fixes
About Company
Skills:
Java, C, C++, Program analysis techniques, Android executables, Large-language model fundamentals, Software security problems and solutions, AI-based binary analysis framework, Android architecture
Skills:
Jax, Pytorch, Python, reinforcement learning
Skills:
Machine Learning, Python, Ubuntu, Linux command line, Robotics simulation
Skills:
causal inference , Jax, Pytorch, Neural ODEs, Bayesian deep learning, Foundation model fine-tuning, Graph neural networks, structural causal models, PINNs methodology, Bayesian experimental design, RL for scientific discovery, causal discovery, active learning acquisition function design, diffusion models
Skills:
Machine Learning, Unsupervised Learning, agentic AI, adversarial machine learning, supervised learning, generative models, reinforcement learning, evaluating frontier AI systems, ML safety, ML interpretability, multi-object optimization, adversarial robustness