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Research Fellow / Engineer, Sustainable Marine Transport

As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT.

The primary responsibility of this role is to deliver on an industry innovation research project where you will be part of the research team a ship route optimization tool and Multiple-Criteria Decision-Making Framework.

The Research Engineer Job scope includes the following:

  1. Executing the Project Tasks with responsibility, diligence, and independence
  2. Publication in journal, presentation in conference
  3. Project coordination with industry partners and attending meeting with project collaborators
  4. Executing other tasks assigned by Project Principal Investigator

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.
  • Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations.
  • Coordinate procurement and liaison with vendors/suppliers.
  • Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.
  • Undertake these responsibilities in the project:

Task 1: Data analytics and machine learning for ship route optimization

Based on the vessels route and weather data, an optimization technique will be employed to suggest an optimal route for shuttle bunkering in Singapore sea. The developed code will take into consideration the vessel velocity, wave and current condition, wind loading and seabed bathymetry in suggesting the optimal vessel route in order to achieve fuel and operational efficiency. the multi-objectives optimization scheme will be utilized in the project to meet the objective functions based on the variables given.

Task 2: Data analytics and machine learning for achieving ship fuel efficiency

The big data analytics and machine learning system will be utilized to predict the fuel consumption of harbor craft vessels based on the weather data and actual ship fuel consumption collected from the mass flowmeter. The task involves considering various machine learning technique or devising new innovative ML technique to accurately predict the fuel consumption of the vessel. This shall aid the ship operators in planning the shipping route that could optimize the fuel consumption, and as a result play an important in mitigating carbon emission.

Task 3: Business Model, Multiple-Criteria Decision-Making Framework

In this task a multiple-criteria framework for the selection of suitable energy conversion systems (including prime mover) on the basis of pertinent cost, environmental and safety considerations will be developed. It is important to highlight that the decision-making model to be developed will take account of the whole life-cycle of the ship (design & construction, operation, disposal). Comparisons of ship performance will be made for different ship energy systems layouts and configurations considered (for example diesel, as compared to diesel-batteries, diesel-electric, LNG-fuelled, etc.). Modern approaches for multiple-criteria decision-making will be reviewed for implementation, with a focus on overcoming shortcomings, in particular the fact that the criteria to be taken into account are usually expressed in different metrics (for example, cost of a prime mover in monetary units vs. emissions expressed as CO2 kilograms emitted). The key processes in this research are to convert all incomparable values into monetary values, thereby enabling the impacts of each criterion to be compared and integrated in a straightforward manner. The multiple-criteria framework will be applied in a number of case studies for the selected ship, examining its applicability for alternative scenarios.

Job Requirements

  • Have a degree in BEng or Master
  • Have knowledge or relevant competence in areas of ship/offshore engineering/marine engineering design
  • Candidates must be well-verse in programming language such as Python/visual basic/matlab etc.
  • Strong analytical skill

Key Competencies

  • 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
  • Show strong initiative and take ownership of work

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