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Field
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candidate holds a Ph.D. in Chemical Engineering (or a related field), is proficient in both mechanistic modeling and ML frameworks (e.g., TensorFlow, PyTorch), and has strong programming skills (Python/MATLAB
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related discipline Experience with CFD software (ANSYS Fluent, OpenFOAM, or equivalent) Familiarity with Python or MATLAB for data processing and ML model development Knowledge of turbulence modelling (RANS
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methods is a plus Programming experience in MATLAB and/or Python Familiarity with process simulation software such as Aspen Plus or Aspen HYSYS Application and Selection: The application folder must contain
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and manage experimental data are essential Prior exposure to manufacturing processes, materials testing, or data analysis (e.g., Excel, MATLAB, or Python) The student should be reliable, able to follow
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English. Ability to supervise students or early-stage researchers. Affinity with data processing techniques and programming (Matlab and/or Python). Hands-on with laboratory work, skilled in experimental
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experimental work in chemical or process engineering (desirable) Knowledge of process optimization, parameter estimation, or control methods is a plus Programming experience in MATLAB and/or Python Familiarity
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/or Python). Hands-on with laboratory work, skilled in experimental design. Creativity, assertive attitude, and perseverance. The selection process will start immediately; the intended start date is in
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Assist with preliminary data review and analysis using tools such as LabVIEW, MATLAB, Python, Microsoft Excel, or similar software. Activities may include plotting pressure and flow data, comparing
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-on experience in the design, construction, commissioning, and operation of complex experimental setups Programming experience in scientific computing environments (e.g., Python, MATLAB) Independent, proactive
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and ML packages with a Python programming environment. Ability to troubleshoot complex biochemical assays, identify causes of non-specific amplification and design appropriate controls. Ability to plan