Research Engineer (Artificial Intelligence) - DW2

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 to develop operation and planning method for onshore microgrid and charging infrastructure within the maritime electrification sector.

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.
• Undertake these responsibilities in the project:
  i. Develop planning optimization method for onshore microgrid and charging infrastructure
  ii. Analyze and develop mathematical models for shore loads and charging demand profiles for electric fleets. This part of the work requires close collaboration with fleet owners based on their needs and operational requirements.
  iii. Analyze charging impact on distribution networks and provide design optimization for charging operators and shore microgrid owners
  iv. Assist supervising student helpers or final year project students participating in the project
• 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.

Job Requirements:

• Have relevant competence in the areas of microgrid/multi-energy Operation and planning, machine learning and data analysis in the field of power system applications.
• Have a degree in Electrical//Electronic Engineering or relevant fields. Possessing a Master’s or PhD degree will be advantageous.
• Proven track record of high quality journal papers published in the relevant field will be highly advantageous.
• Knowledge of optimisation algorithm development in the field of power systems will be advantageous.
• Familiarity with optimisation using Gurobi, Cplex and etc. is a must.

Key Competencies:

• Able to build and maintain strong working relationships with people within and external to the university.The project is an industry facing one where frequent interactions and information exchanges are required with industry partners.
• 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