Research Fellow, Machine Learning / Natural Language Processing / Web Scraping
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 an automated profiling and functional characterization platform for plant-based protein ingredients in food and beverages. To this end, you will be involved in the computational part of the project by:
- analyzing data on the key protein properties generated by our experimental team, using data analytics or machine learning techniques,
- linking protein sequences, mass spectrometry data and structural information to their properties, using advanced natural language processing (NLP) models (e.g., BERT, transformer, etc.)
- performing web scraping to generate additional data on the key protein properties from open literature, for comparison and analysis
- 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. Generate and maintain a database of the proteins’ key functional properties measured under different experimental conditions by the team
ii. Perform supervised and unsupervised learning from the database
iii. Analyze protein sequences and mass spectrometry data from our collaborators and link them to protein properties, using advanced NLP models
iv. Perform web scraping to generate additional data from open literature for comparison and analysis
v. Present research findings in meetings with industrial collaborators or conferences; prepare peer-reviewed publications on the findings.
vi. Engage and communicate with vendors/suppliers for purchasing equipment and visit vendors’ facilities for both equipment evaluation and training purpose.
- 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.
- PhD in Chemical Engineering, Computer Science / Engineering or related fields. Master’s degree candidates with significant computational research experience may also be considered.
- Proficiency in performing machine learning on large, multimodal, and multivariate data sets. Previous experience with deep learning using neural networks / NLP / web scraping would be advantageous.
- Interest and enthusiasm for academic research to be applied in the food industry.
- Good interpersonal, communication and technical writing skills. Good problem-solving skills.