CFD & ML

Job Description

PhD Research Position – CFD & Machine Learning for Nanofluid Thermal Performance | VIT Chennai
Organization

Vellore Institute of Technology (VIT), Chennai

School: School of Mechanical Engineering

Research Group: Computational Fluid Dynamics (CFD) Research Group

Position

PhD Research Scholar

Research Area

Computational Fluid Dynamics (CFD) and Machine Learning for Nanofluid Heat Transfer

Research Overview

The PhD research focuses on improving the thermal performance of nanofluids using a combination of Computational Fluid Dynamics (CFD) and Machine Learning (ML) techniques.

The research aims to:

Improve heat transfer efficiency.
Develop high-fidelity CFD models.
Apply Machine Learning for predictive thermal analysis.
Optimize nanofluid performance under different operating conditions.
Support applications in thermal management, cooling systems, and energy engineering.
Research Objectives

The selected candidate will work on:

Thermal performance analysis of nanofluids.
Multiphase turbulent flow modeling.
Nanoparticle shape effect analysis.
Convective heat transfer simulations.
Nanoparticle dispersion modeling.
CFD simulation development.
Machine Learning model development for thermal prediction.
Integration of CFD with data-driven AI models.
Key Responsibilities
Computational Fluid Dynamics (CFD)
Develop CFD models.
Perform fluid flow simulations.
Conduct heat transfer analysis.
Simulate multiphase turbulent flows.
Analyze nanoparticle dispersion.
Validate CFD models.
Machine Learning
Build predictive ML models.
Analyze CFD-generated datasets.
Optimize thermal performance using AI.
Integrate ML with CFD simulations.
Develop data-driven prediction frameworks.
Research Activities
Literature review
Numerical modeling
Data analysis
Scientific documentation
Journal publications
Conference presentations
Required Qualifications
Master’s Degree Candidates

Eligible degrees:

M.Tech in Mechanical Engineering
M.E. in Mechanical Engineering
M.Sc.
Thermal Engineering
Applied Mathematics
Related disciplines
Bachelor’s Degree Candidates

Eligible degrees:

B.E. Mechanical Engineering
B.Tech Mechanical Engineering
Aeronautical Engineering
Automobile Engineering
Preferred Technical Skills
CFD Software
ANSYS Fluent
OpenFOAM
Programming
Python
MATLAB
C
Engineering Knowledge
Fluid Mechanics
Heat Transfer
Thermodynamics
Multiphase Flow
Turbulence Modeling
Machine Learning

Experience or interest in:

Predictive Modeling
Data Analytics
Machine Learning Algorithms
Scientific Computing
Soft Skills
Strong analytical thinking
Research aptitude
Scientific writing
Technical communication
Problem-solving
Independent research capability
Fellowship
For Master’s Degree Holders
Year 1: ₹31,000/month
Years 2 & 3: ₹35,000/month

Duration: 3 Years

For Bachelor’s Degree Holders
Years 1 & 2: ₹21,000/month
Years 3 & 4: ₹30,000/month

Duration: 4 Years

Additional Benefits
Raman Research Award up to ₹1,00,000 for outstanding publications.
Financial support for:
Conference presentations
Journal publications
Opportunity to work on advanced interdisciplinary research combining CFD and AI.
Research Domains
Computational Fluid Dynamics (CFD)
Machine Learning
Artificial Intelligence
Heat Transfer
Nanofluids
Thermal Engineering
Energy Systems
Cooling Technologies
Scientific Computing
Ideal Candidate Profile

The ideal applicant should have:

Strong background in Mechanical or Thermal Engineering.
Knowledge of CFD simulations.
Programming skills in Python, MATLAB, or C.
Interest in applying Machine Learning to engineering problems.
Passion for academic research and scientific publications.
Application Process

Interested candidates should submit:

Updated CV/Resume
Contact details of at least two academic or professional references

Application Email: harish.r@vit.ac.in