Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
field. Have proven expertise in statistical modelling and machine learning for large and complex datasets. Have proficiency in Python and/or R for time-series and sensor data analysis. Have an interest in
-
of scientific findings. He/she will be accountable to the Principal Investigator (PI). The RF / RA will be able to: Conduct quantitative data analysis using SPSS / STATA / R; Lead the development of research
-
experience in programming languages such as R, Python, and familiarity with NLP tools and techniques (essential) Proven track record in handling and analyzing large healthcare dataset (essential) Track record
-
projects. Disseminate research findings through conferences, invited talks, and outreach activities, strengthening NTU’s leadership in infrastructure security R&D. Job Requirements: A PhD in Computer
-
researchers involved in security-related projects. Disseminate research findings through conferences, invited talks, and outreach activities, strengthening NTU’s leadership in infrastructure security R&D. Job
-
infrastructure security R&D. Job Requirements: A PhD in Computer Science, Software Engineering, Artificial Intelligence, or a related discipline. Proven research track record demonstrated by publications in top
-
SPSS and R, and proficient in graphical-user interfaced software (e.g. Qualtrics, Verint, Google forms, Microsoft Office suite) We regret to inform that only shortlisted candidates will be notified
-
framework such as Tensorflow, Pytorch, MXNet and Programming Languages such as Python, Matlab, R and/or C/C++. Demonstrated project experience related to causal inference will be an advantage. Good written
-
Requirements Possess a PhD degree in Environmental Engineering or related field. Has relevant R&D experiences in RAS system for aquaculture system. Open to fixed-term contract More Information Location: Kent
-
studies, QTL studies, colocalization, Mendelian Randomization) Proficient in R, Python, Linux/Unix Command over commonly used genetics (e.g., PLINK, GCTA, FUMA, variant predictor tools) and metagenomics