-
experience in photonic device design, numerical simulation, and layout. Proficiency with relevant design and simulation tools, such as Ansys Lumerical, COMSOL, MATLAB, or Python. Hands-on experience in
-
computational methods for engineering analysis. Proficiency in scientific programming, preferably using Python, MATLAB, C/C++, or comparable programming languages. Experience with advanced sampling methods
-
will bridge rigorous theoretical work with hands-on offloading algorithm design and development. The core responsibility is to build and validate these offloading strategies, complete with Python
-
methods for additive manufacturing applications, including ANNs and evolutionary genetic algorithms for process optimization supported by programming knowledge (e.g. Matlab, Python). Hands-on experience
-
engineering / technical hands-on experience soundscape evaluation Familiarity with soundscape ISO standards Good written and oral communication skills Proficiency in AI (python) programming and R programming
-
materials characterization (e.g., SEM, XRD, FTIR, mechanical testing). Proficiency in data analysis tools (Python, MATLAB, JMP) and technical documentation. Strong analytical skills and attention to detail
-
/scholarships/nus-research-scholarship/) • Strong written and spoken communications. • Demonstrated strong research interest, skills, and experience. • Proficiency in programming languages (e.g., Python
-
and convex optimization. Prior experience in software development in machine learning systems is highly desirable. Proficient in Python and ML frameworks such as PyTorch. Independent, highly analytical
-
Python programming is an advantage Good written and oral communication skills Ability to work independently and good time management skills If you share our interest in leveraging first-principles
-
programming skills in Python and/or R; experience with STATA, MATLAB, or SQL is advantageous. Experience with aviation, airport, airspace, flight trajectory, or transportation datasets. Strong publication