10 data-analytics-phd Fellowship research jobs at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) in United Kingdom
Sort by
Refine Your Search
-
Requirements PhD in Geography, GIS, Remote Sensing, Environmental Science, Earth Science, or related disciplines. Strong working knowledge of GIS platforms (e.g., ArcGIS, QGIS) and spatial data analysis
-
renewable energy. Responsibilities include calibrating simulations with experimental/numerical data, performance analysis, and contributing to interdisciplinary research on coastal protection, with
-
stability. Experience in designing connectors or mechanical interfaces is a plus. Familiarity with 3D printing technologies and materials is advantageous. Strong analytical skills and familiarity with data
-
for amino acid profiling, polyphenol profile analysis, SDS-PAGE, and protein hydrolysis. Have a degree in Food Science and Technology, or Analytical Chemistry. Possessing a Master's or PhD degree will
-
/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related disciplines. Knowledge of autonomous vehicles or cyber security will be
-
, data collection, and analysis. Industry or research lab experience is required. Strong analytical and conceptual abilities. Ability to work in a team as well as independently. Able to work under pressure
-
with Principal Investigator (PI) and the research team members to ensure all project deliverables are met. Prepare data collection forms/interview questions/questionnaire and recruit and/or interview
-
(Research Engineer) Bachelor/Master degree in Computer Science or a related field Proven ability to conduct independent research with a relevant publication record. Outstanding data analytics, mathematical
-
will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
-
experimental data, analyzing shear coefficients and drag forces, and contributing to interdisciplinary research on coastal protection, with an emphasis on delivering accurate and impactful modeling insights. Key