114 parallel-programming-"Uppsala-University" Fellowship positions at Nanyang Technological University
Sort by
Refine Your Search
-
Fellowship Programme) and with external partners. Job Requirements: Candidates must have a PhD in one of the relevant fields of Asian Studies, international political economy, political science, public policy
-
Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
-
of programming languages such as matlab and Python. We regret to inform that only shortlisted candidates will be notified. Hiring Institution: NTU
-
Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
-
The role is part of NTU's Experimental Asset Markets group in the Economics Programme at the School of Social Sciences. The team focuses on lab experiments simulating asset markets to study pricing
-
. Perform any other duties relevant to the research programme. Job Requirements: PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive
-
programming languages such as C and Python Proficiency in deep learning frameworks such as Pytorch and Tensorflow Knowledge in imaging and computing device and equipment Good written and oral
-
other duties relevant to the programme of research. Job Requirements: PhD degree or at least 8 years working experience in Computer Engineering, Computer Science, Electronics Engineering or equivalent
-
Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
-
communication, or signal processing. Proficiency in programming languages like Python, MATLAB, or C++, and experience with AI/ML frameworks like TensorFlow, PyTorch, or scikit-learn. A proven track record of