Job Description

The School of Materials Science & Engineering (MSE) invites applications for the position of Research Assistant. Key Responsibilities: * To be familiar with semi structured interview protocols and The School of Materials Science & Engineering (MSE) invites applications for the position of Research Assistant. Key Responsibilities: To be familiar with semi structured interview protocols and conduct interviews independently literature review and summarize the main findings from the literature To conduct field observation (e.g., classroom observation) independently To conduct qualitative (e.g., systematic literature review, video analysis) and quantitative data analysis (e.g., statistical modeling and analysis) To draft research reports and conference/journal papers To organize PD sessions as needed, manage project items (e.g., video recorders, cameras) To perform other administrative duties where necessary. To perform tasks as required by the PI or co-PI Job Requirements: At least a bachelor's degree in social science fields (e.g., education, psychology, communication, art). A masters/doctoral degree is preferable. Interest in the following concepts including educational psychology, teaching and learning etc Proficiency or understanding at least with the two of the following fields: (1) Education, (2) Design thinking, (3) engineering education, (4) engineering design process, and (5) educational psychology. Knowledgeable in two of the following concepts: (1) Education psychology theories (e.g., social cognitive theory, social cognitive career theory, pedagogical content knowledge, theory of planned theory), (2) assessment, (3) teaching and learning methods (e.g., inquiry-based learning, problem-based learning), and (4) curriculum theory & co-constructed lesson designs. Ability to conduct scientific research and literature review under minimum supervision Proficient communication and writing skills Background/Experience in qualitative (e.g., systematic literature review, video analysis) and quantitative data analysis (e.g., statistical modeling and analysis) For further details, please email Prof Eileen Fong (PI) at , or Prof Ibrahim H. Yeter (Co-PI) at We regret that only shortlisted candidates will be notified.