Position: AI4CFD Research Associate (Part-time) of Polyu

Project Overview: We are currently engaged in a research project that combines 
Artificial Intelligence (AI) and Computational Fluid Dynamics (CFD), with the 
goal of enhancing the performance of CFD simulations through AI technology.

Job Description: We are recruiting undergraduate, master's, or doctoral students 
to serve as AI4CFD Research Associate (Part-time) to assist in project-related 
work, primarily including data processing, model training, and result analysis.

Job Responsibilities:

Assist in collecting, cleaning, and preprocessing CFD data.
Participate in the development and optimization of AI algorithms to improve the 
accuracy and efficiency of CFD simulations.
Train and evaluate models.
Write research reports and assist in writing academic papers.
Qualifications:

Bachelor's, Master's, or Doctoral students in Computer Science, Fluid Mechanics, 
Applied Mathematics, or related fields.
Candidates familiar with the basics and applications of CFD will be given 
preference.
Candidates with programming experience in languages such as Python, C++ will be 
given preference.
We Offer:

Competitive remuneration (negotiable).
Flexible working hours.
Application Method:
Please send your personal profile to: zhaokun.wang@connect.polyu.hk. Please 
indicate "AI4CFD Research Assistant - Your Name" in the email subject; or 
contact directly via WeChat: 13126719732.

Deadline: December 8, 2024.

We look forward to collaborating with you to explore the endless possibilities 
of combining AI and CFD!

Applications are invited for several PhD studentships at the Southern University of Science and Technology 
(SUSTech) in Shenzhen, China. Successful candidates will become members of the Multicomponent Fluids 
Group (McF) and will collaborate with Dr. Huanshu Tan, Assistant Professor at both the Department of 
Mechanics and Aerospace Engineering (MAE) and the Center for Complex Flows and Soft Matter Research 
(Center).

Project Descriptions
PhD research projects are available in the following areas (but not limited to):
1. Interfacial Flows of Multicomponent Fluids:
Self-propelling phenomena and flow control;
   An integrated experimental and numerical study.
2. Complex Drop & Bubbles:
   Liquid-liquid phase separation and evaporation/dissolution;
   An integrated numerical and experimental study.
3. Microfluidics:
   3D-printed micro-device for interfacial control and colloidal manipulation;
   Mainly experimental study focusing on innovation for applications.

About SUSTech 
Southern University of Science and Technology (SUSTech) is a public university, located in the scenic hills of 
Nanshan District, Shenzhen. It aspires to become a world-class university excelling in interdisciplinary 
research, nurturing innovative talents, and delivering new knowledge to the world. SUSTech achieved the 4th 
position among the world's 100 fastest-rising organizations in “Nature Index 2022 Rising Stars” and holds the 
No.1 spot among young universities established after 1988. According to the Times Higher Education World 
University Rankings, SUSTech has consistently ranked among top 15 universities in mainland China since 
2018. The 2024 QS World University Rankings placed SUSTech 15th in mainland China.

More information about SUSTech, the MAE Dept., the Center, and Dr. Huanshu Tan can be found at:
https://www.sustech.edu.cn/en/
https://mae.sustech.edu.cn/en/
https://compflow.sustech.edu.cn/en_index.html
https://faculty.sustech.edu.cn/tanhs/en/
https://scholar.google.com/citations?hl=en&user=S8ocYrwAAAAJ&view_op=list_works


About the Programs
1. SUSTech provides Doctoral Programs conduced in English, specifically designed  for international students.
2. The Doctoral Programs are typically expected to be completed within a four-year timeframe. 
3. For the latest information on SUSTech supervisors and 
research areas, kindly visit the official webpage. The 2024 information is currently 
available(https://gs.sustech.edu.cn/#/admission/en/cooperation), and details for 2025 will be released soon.


Enquiries
Fro prospective applicants interested in the PhD program, please submit the following documents via email to 
Dr Huanshu Tan (Contact: tanhs@sustech.edu.cn)

1. Cover Letter
   Include a cover letter that details your qualifications and expresses your interest in the PhD program and 
specific projects.
2. Curriculum Vitae (CV):
    Provide a comprehensive CV that outlines your education and research experience.
3. Referee Contact Details:
   Include the contact details of two referees who can speak to your academic and research qualifications.

Submit the above documents to :
Contact: Dr. Huanshu Tan
Email: tanhs@sustech.edu.cn


For general enquiries, please contact:
SUSTech Graduate School Admissions and International Office
Email: pgadmissions@sustech.edu.cn 
SUSTech official website: http://www.sustech.edu.cn/en

Are you ready to make a real-world impact through cutting-edge research? A fully 
funded PhD scholarship for Commonwealth applicants is now open, with a deadline to 
apply by 16th December 2024.

This is your chance to contribute to the development of clean energy technologies 
and play a pivotal role in tackling global challenges like climate change and 
sustainable transportation. By working on CFD simulations for advanced propulsion 
systems and or thermal management for clean energy technologies, your research can 
drive innovation in energy efficiency and green technologies, shaping a more 
sustainable future for generations to come.

As your supervisor, I will guide you through this impactful journey, helping you 
create meaningful solutions that benefit society and industry alike.

For inquiries and guidance on your application, please contact:
📧 mohammad.moghimi-ardekani@staffs.ac.uk

Together, let’s make a difference in advancing sustainable energy solutions!

Are you ready to make a real-world impact through cutting-edge research? A fully 
funded PhD scholarship for Commonwealth applicants is now open, with a deadline to 
apply by 16th December 2024.

This is your chance to contribute to the development of clean energy technologies 
and play a pivotal role in tackling global challenges like climate change and 
sustainable transportation. By working on CFD simulations for advanced propulsion 
systems and or thermal management for clean energy technologies, your research can 
drive innovation in energy efficiency and green technologies, shaping a more 
sustainable future for generations to come.

As your supervisor, I will guide you through this impactful journey, helping you 
create meaningful solutions that benefit society and industry alike.

For inquiries and guidance on your application, please contact:
📧 mohammad.moghimi-ardekani@staffs.ac.uk

Together, let’s make a difference in advancing sustainable energy solutions!

Position Overview:

We are seeking a motivated and detail-oriented intern to join our research team. 
The successful candidate will work on a project focused on analyzing the 
turbulence effects on the pickling process using Computational Fluid Dynamics 
(CFD) with ANSYS Fluent. This internship offers a unique opportunity to gain 
hands-on experience in CFD modeling and simulation, as well as to contribute to 
meaningful advancements in industrial processes.


Key Responsibilities:

•	Conduct literature reviews to understand the current state of research 
on turbulence effects in pickling processes.
•	Develop and validate CFD models using ANSYS Fluent to simulate the 
pickling process.
•	Analyze simulation results to identify key factors influencing 
turbulence and their impact on the efficiency and quality of the pickling 
process.
•	Collaborate with the research team to design experiments and validate 
simulation results.
•	Prepare technical reports and presentations to communicate findings and 
recommendations.


Additional Information:

•	Paid Internship
•	Duration: 6 months
•	Start: February 2025
•	Location: ArcelorMittal R&D center at Maizieres-les-Metz (57280, France)
•	Transport: Public transport is available
•	Internship supervisor: Oliver Scorsim (oliver.scorsim@arcelormittal.com)


Please send your application (CV and cover letter) by email to internship 
supervisor.

A PhD student position is potentially available (depending on funding 
availability) in as early as Spring 2025 or Fall 2025 semester at the City 
College of New York (CCNY) of the City University of New York (CUNY). The 
research aims to develop new and enhanced existing numerical models for problems 
with coastal ocean flows and fluid-structure interaction. It is expected that 
the candidates are highly motivated and goal-oriented and have

   1. MS degree in mechanical/civil/ocean engineering, or applied math, or other 
related disciplines
   2. Solid knowledge in mathematics and physics

Experience in computer programming (e.g., Fortran, C++, Python) and flow 
modeling and algorithms is preferred. Background in both math and engineering is 
especially welcome. People with citizenship of the U.S. and its territories may 
have priority. 

CUNY is the US’s leading urban public university, serving 200,000 students at 25 
colleges in New York City. CCNY, the university's flagship campus, is located in 
Manhattan and draws students from around the world. CCNY is ranked among the top 
US universities for producing engineers, business executives, and scientists 
(including over 10 Nobel Prize winners and Fields medallists).

If interested in this potential position, please email a CV with “Ph.D. 
position” in the subject line to htang@ccny.cuny.edu. This is a continued search 
from a few months ago, and those who have sent C.V. before don’t need to send it 
again, and are thanked. All received CVs will be reviewed together. After 
position is available, only those who match the job will be contacted. 

An immediate postdoctoral position is available at the FAMU-FSU College of 
Engineering for a collaborative project with national laboratories.

We are seeking applicants with expertise in:
	•	Complex fluids
	•	Particle suspensions
	•	Rheology
	•	Numerical methods (e.g., finite element methods, lattice Boltzmann 
methods, dissipative particle dynamics)

While experience with deep learning is not required, it will be considered a plus. 
The position is renewable contingent on satisfactory progress. Successful project 
completion may lead to potential employment opportunities within the national lab 
system.

Interested candidates should submit their application by including a CV, a brief 
statement of research interests, and contact information for references through 
the email listed below. 

Postdoctoral Research Fellow - Multiscale Material Modelling and Design
Location: University of Tennessee Chattanooga
Duration: Three-year contract, renewable for up to 5 years
Start Date: 08/01/2025
Position Overview: Micro/nano-Engineering Laboratory at University of Tennessee 
Chattanooga is seeking a motivated and innovative Postdoctoral Research Fellow 
to join our team in development of accurate characterizations and discoveries 
for nanomaterial with customizable properties. The successful candidate will 
work on multiphysics and multiscale simulations, and machine learning guided 
design and experiments of functional nanomaterials for energy, bioengineering 
and defense applications.
Key Responsibilities:
•	Develop and implement multiscale simulation models, machine learning 
guided design, and experimental characterization.
•	Analyze and interpret data, and prepare results for publication in peer-
reviewed journals.
•	Present findings at conferences and contribute to proposals for external 
funding.
•	Mentor undergraduate and/or graduate students.
Preferred Qualifications:
•	A Ph.D. in Mechanical Engineering, Materials Science, Chemistry, or 
related discipline.
•	Experience with one or more areas: density functional theory, molecular 
dynamics, computational fluid dynamics, computational solid mechanics, high-
performance computing and nanoporous materials characterization. 
•	A track record of peer-reviewed publications in reputable journals.
•	Excellent written and verbal communication skills.
•	Ability to work collaboratively in a multidisciplinary research 
environment.
•	Interest in mentoring and outreach activities.
What We Offer:
•	Access to state-of-the-art facilities and resources, including HPC 
clusters and advanced microscopy facilities.
•	Collaboration opportunities with leading experts, including partners at 
Oak Ridge National Laboratory, and Department of Energy.
•	A supportive and dynamic research environment with opportunities for 
professional development.
Application Instructions:
Interested candidates should submit the following documents in a single PDF:
1.	A cover letter summarizing research interests and career goals.
2.	A detailed CV, including a list of publications.
3.	Contact information for three references.

Submit Applications To: utc.nanoengineering@gmail.com

SANTANA Project: Advanced parallel linear solvers for the CFD simulation 
software CODA

This research project will investigate iterative solvers for use in the software 
suite CODA developed by Onera, Airbus and DLR under the SANTANA project. CODA is 
a CFD solver for aircraft design and it features innovative algorithms as well 
as advanced software technology concepts dedicated to HPC. The Spliss library, 
used in CODA to handle linear algebra problems, provides an excellent framework 
for parallel computing. However, the high number of iterations currently 
observed for the block-Jacobi preconditioned Newton-Krylov solver clearly 
indicates that further improvements are necessary. In this project, we will 
carefully analyze and identify bottlenecks using the mathematical structure of 
the system and its HPC implementation.

There is a wide range of algorithmic choices in the literature that can enable 
algorithmic improvements and hence faster and more robust convergence. These 
include advanced domain decomposition techniques as well as modern multi-level 
and multi-grid methods, possibly combined with modern low-density direct 
methods.
While these algorithms can serve as efficient preconditioners, we will also 
explore advanced Krylov subspace techniques, including subspace recycling 
techniques over time steps and deflation techniques to overcome  convergence 
blocking. Recently randomized linear algebra has shown promise in efficiently 
solving implicit RANS equations using Newton-Krylov methods and will be 
investigated in this project for its feasibility in CODA. The selected improved 
solvers will be integrated into the CODA tool, possibly based on interfacing 
with existing libraries. The post-doc researcher in this position is expected to 
collaborate closely with another researcher working on the same project.


Skills required:
•You have defended your thesis less than 3 years from the date of this job 
offer.
• PhD in applied mathematics, fluid dynamics, computer science, iterative 
solvers, numerical linear algebra,
high performance computing.
• Knowledge of preconditioners applied to large-scale problem
• Proficiency in programming languages C++ and Python.
• Familiarity with HPC environments and performance optimization.

To apply, please send your CV and covering letter to carola.kruse@cerfacs.fr, 
applications are open until 03/03/2025.

https://cerfacs.fr/en/offer/santana-project-advanced-parallel-linear-solvers-
for-the-cfd-simulationsoftware-coda/