Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
, finance or computing science/natural language processing/machine learning. Preference will be given to those who are proficient in Python, adept at processing large-scale data and have worked with large
-
English. Preference will be given to those with (i) strong background in quantitative methods, geospatial methods, AI and machine learning; (ii) experience in high-performance and cloud computing; (iii
-
Duties Teach any of the following postgraduate course(s) in the upcoming Semester A 2024/25 and/or Semester B 2024/25: Statistical Machine Learning I Statistical Machine Learning II Exploratory Date
-
teaching duties. Applicants should possess a PhD degree in Computer Science, Computer Engineering, Information Systems, or a related field, and sufficiently demonstrate abilities to conduct high-quality
-
teaching duties. Applicants should possess a PhD degree in Computer Science, Computer Engineering, Information Systems, or a related field, and sufficiently demonstrate abilities to conduct high-quality
-
., MATLAB, Python) is required. Experience with machine learning is highly preferred. Ability to work independently and as part of a team. Key Requirements for PhD: Hold a Bachelor's degree with outstanding
-
proficiency in machine learning, statistical modeling, and data analysis using Python, R, or similar platforms. Experience in grant proposal writing, scholarly manuscript preparation, and psychological
-
computing, and to pursue new strategic research initiatives under the Department/Faculty/University. Requirements: Applicants should possess a PhD degree in Computer Science, Computer Engineering, Information
-
for the captioned post. Duties and Responsibilities Develop and apply advanced artificial intelligence and machine learning models to real-world data (RWD). Create innovative tools and solutions to extract deeper
-
. Proficiency in SQL, Python/R, or similar tools; experience with big data platforms , machine learning, and data warehousing. Commitment to quality, integrity, confidentiality and compliance. Excellent