Job Description

Mengaldo’s Laboratory is looking for a self-motivated, proactive and highly creative Research Engineer that will be working towards earning a PhD degree at NUS in explainable machine learning for sequential data and time series. 

The ideal candidate should be skilled in coding, and software development, and be highly proficient in  Python, Tensorflow or Pytorch, large-scale sequential-data analysis (including time series), neural networks, explainable AI.

The project is in collaboration with University of Geneva, (Switzerland), Scuola Superiore Sant’Anna (Italy), National Institute of Geophsyics and Vulcanology (Italy), and University of Cambridge (United Kingdom), the latter starting from 2023. The primary objective of the project is to provide novel interpretability methods for classification and regression tasks using neural networks, and deployed to sequential and time series data. Main areas of application include: healthcare, physics, and finance.

Qualifications

• Bachelor in Computer Science, Applied Mathematics, Physics, Engineering, or related fields.
• Good problem-solving skills.
• Proficient in English writing and verbal communication skills.
• Coding and software development (Python, Tensorflow or Pytorch).
• Natural Language Processing.
• Neural networks.
• Large-scale spatio-temporal data analysis.
• Weather and climate.

Covid-19 Message

At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presence is required.

Taking into consideration the health and well-being of our staff and students and to better protect everyone in the campus, applicants are strongly encouraged to have themselves fully COVID-19 vaccinated to secure successful employment with NUS.

More Information

Location: Kent Ridge Campus
Organization: College of Design and Engineering
Department : Mechanical Engineering
Employee Referral Eligible: No
Job requisition ID : 17417