Singapore Institute of Technology (SIT)

Research Fellow/Engineer (Physics-Informed Neural Network (PINN)) - EA4

2023-12-31 (Asia/Singapore)
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Key Responsibilities

  • •Participate in and manage the research project with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met.
  • Meeting the project deliverables within the project timeframe, which consists of the following responsibilities:
    o Designing and programming the PINN algorithm in python specifically targeted at conjugate heat transfer application
    o Design and perform experiment, including selecting and rigging up sensor network, to accelerate PINN solution
    o Perform computational fluid dynamics (CFD) runs for validation of PINN solution
    o Improve efficiency of the PINN algorithm
  • Assists in co-supervision of Final Year Projects (FYP) or capstone projects students together with the project PI
  • Assists PI in drafting of reports, conference proceedings and journal articles based on the outcome of the projects
  • Prepares and shares fortnightly report of results from project work with PI
  • Support and coordinate procurement and maintenance of the software/hardware under the charge of the PI
  • Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations.
  • Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.


  • Have relevant competence in the python programming, internet of things (IoT) setup, sensors integration, python programming
  • Familiar with data analytics software and platforms like JupyterLab, SciPy ecosystem, scikit-learn libraries, tensorflow libraries.
  • Knowledge in Computational Fluid Dynamics, ability to use OpenFOAM is a bonus
  • A good Bachelor, Masters or Ph.D degree in Data Science or Computer Engineering or Electrical Engineering from a reputable university.
  • Fluent verbal and written communications.

Key Competencies

  • Good self-discipline and motivated to deliver
  • Show strong initiative and take ownership of work
  • Able to build and maintain strong working relationships with people within and external to the university.
  • Self-directed learner who believes in continuous learning and development
  • Proficient in technical writing and presentation
  • Possess strong analytical and critical thinking skills

Advertised: 26 Apr 2023 Singapore Standard Time
Applications close: 31 Dec 2023 Singapore Standard Time

Dettagli del lavoro

Research Fellow/Engineer (Physics-Informed Neural Network (PINN)) - EA4
10 Dover Drive , Singapore
Scadenza candidatura
2023-12-31 23:59 (Asia/Singapore)
2023-12-31 16:59 (CET)
Tipo di lavoro
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Singapore Institute of Technology aims to be a leader in innovative university education by integrating learning, industry and community.

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