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Research Assistant (AI, Technology, Medicine)
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The Division of Information Technology and Operations Management at Nanyang Business School is inviting applications for a Research Assistant position.
Job Responsibilities:
The RA is expected to plan, organize and implement research projects, in collaboration with the principal investigators. The successful candidate will work closely with professionals in the field of AI, technology and medicine.
Conduct literature reviews, coordinate schedules for data collection with survey and interview participants
Assist in data collection, data transcription and analysis
Contribute to the dissemination of research findings
Job requirements:
Minimally a bachelor's degree in a related field (i.e. Business, AI, Technology or Medicine)
Excellent oral and written communication skills are required
Able to work independently and meet deadlines
Experience with qualitative methods and data analysis
We regret to inform that only shortlisted candidates will be notified.
Job ID: 151632681
Skills:
Data Analysis, qualitative methods, data transcription, Data Collection, AI technology
Skills:
technology sales , Cloud Solutions, It Services, Digital Transformation, Technology Consulting, Lead Generation, GenAI Solutions, Managed Services, Business Development, AI Solutions
Skills:
Powerbi, Data Analysis, Aha, Microsoft Office Suite, project management tools
Skills:
System Security, Docker, Python, Data Analytics, BigQuery, Machine Learning, Google Cloud Platform, Cybersecurity, Git, Iam, Kubernetes, Linux environments, explainable AI, TensorRT, anomaly detection, ONNX, Vertex AI, edge AI deployment, GANs, security-log analysis, generative AI techniques, AI-assisted decision support systems, NVIDIA Jetson, authentication systems, ARM platforms, tabular data modeling, security analytics, diffusion models
Skills:
test equipment , Test Architecture, Data Analysis, Reliability Testing, AI ML tools, packaging fail modes, Simulation Tools, electrical failure analysis, ASIC product testing, DFT strategies, material interaction and properties, Statistics, Statistical Modeling, package characterization, semiconductor packaging process
