191 parallel-computing-numerical-methods-"Simons-Foundation" Fellowship positions at Nanyang Technological University
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
nonlinear optical applications. The roles of this position include: Conduct theoretical and numerical research and develop theoretical models for low-dimensional material nanophotonics. Apply numerical models
-
and outdoor environments. Mandatory Requirements: Ph.D. in Robotics, Computer Science, Electrical Engineering, or related fields, with a focus on Path Planning, Multi-Robot Systems, or Autonomous
-
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 School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational
-
half of them published in prestigious journals (Chem. Eng., Appl. Energy, Energy Convers. Manag., Renew. Sustain. Energy Rev.). His contributions have earned his numerous fellowships and awards
-
to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
-
in Health Research Methods, Epidemiology, Computer Science, or a related field. Expertise in evidence synthesis and clinical guideline methodology such as network meta-analysis, GRADE. Experience with
-
, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
-
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
-
, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems