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 a flexible array ultrasound imaging system for velocity estimation.

Key Responsibilities:

• Participate in and manage the research project with Principal Investigator (PI), Collaborator and the research team members to ensure all project deliverables are met.
• Undertake these responsibilities in the project:
  i. To develop simulation models for flexible array ultrasound system
  ii. To develop custom phantoms for experimental studies
  iii. To design and develop non-linear signal processing algorithms including deep learning algorithms for image reconstruction
• 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 digital electronics, signal processing, machine learning and deep learning.
• Have a B-Engg or B. Tech degree in Electronics, Computer or Biomedical Engineering with undergraduate projects related to the relevant competence mentioned.
• Knowledge of biomedical signal processing will be advantageous.
• Should have proficiency in Matlab or Python.
• Prior experience in publishing is desirable.

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

Major Challenges

• Integration of flexible arrays with research ultrasound platform
• Design and development of deep learning-based flexible array adaptive image reconstruction pipeline