Are you looking to apply your expertise in Computational Fluid Dynamics (CFD) or 
AI-driven manufacturing in a dynamic industry setting?

The University of Leeds and Morvern Group Ltd. have an exciting opportunity for 
a high-calibre graduate to lead a Knowledge Transfer Partnership (KTP) project. 
This KTP will drive the transformation of ceramic core manufacturing for 
aerospace and industrial gas turbine components using advanced computational and 
AI methodologies.

This role will be based at the Morvern Group Ltd, Morvern House, Denby Hall 
Business Park, Ormonde Drive, Derby, DE5 8LE working with the School of 
Mechanical Engineering within the Faculty of Engineering and Physical Science at 
the University of Leeds.

This position offers a unique opportunity to work on an industry-led innovation 
project, applying leading academic research to real-world challenges. As a KTP 
Associate, you will be instrumental in embedding novel computational modelling 
solutions within Morvern Group Ltd. This role provides a fast-track career 
development opportunity, with access to training and mentoring from both 
academic and industry experts

Morvern Group is a fast growing and innovative company that specialises in high-
precision manufacturing for the aerospace and industrial gas turbine sectors. 
With a focus on cutting-edge technology, Morvern Group is committed to 
delivering high-quality, bespoke engineering solutions to its customers.

By working between the University of Leeds and Morvern Group, the successful 
candidate will gain a unique blend of academic insight and industrial 
application, developing technical and project management skills while 
contributing to transformative manufacturing innovation.

Visa Entitlement 

Please note that this post may be suitable for sponsorship under the Skilled 
Worker visa route but first-time applicants might need to qualify for salary 
concessions. For more information please visit: www.gov.uk/skilled-worker-visa.

For research and academic posts, we will consider eligibility under the Global 
Talent visa. For more information please visit: https://www.gov.uk/global-talent

What are the benefits of being a KTP Associate?

Freedom to lead, develop and implement innovative solutions and cutting-edge 
research at the heart of energy related industry.
KTP Associates spend 10% of their time on Personal Development, making full use 
of a £4,000 PD budget.
Experience of cutting-edge consumer research techniques and project management.
Access to two residential training sessions aimed at developing project 
management skills.
Opportunity to gain both management and academic experience.
Potential to fast-track a career in industry.
Access to a wealth of academic resources.
Access to a Travel & Subsistence and Consumables budget.
Access to mentoring sessions through Innovate UK.
To explore the post further or for any queries you may have, please contact:

ACADEMIC SUPERVISOR

Dr Zinedine Khatir - Assistant Professor, Email: Z.Khatir@leeds.ac.uk

COMPANY SUPERVISOR

Mark Urch – Operations Director, Email: Mark.Urch@tarpeyharris.com 

UoL KTP OFFICE

James Hartford, Innovation Support Co-ordinator (University of Leeds), Email: 
J.Hartford@leeds.ac.uk

The Centre on Sustainable Energy (SE) is looking for a young student interested 
in carrying out an internship/master thesis experience in the field of 
batteries. The ideal candidate is a proactive and dynamic person with good 
organizational skills, a strong interest in physics, modeling and computer 
science and, of course, motivated to have research experience in an 
international context. 
 
The internship/master thesis will focus on multiphysics modeling of redox flow 
batteries. Redox flow batteries (RFBs) are a promising technology for large 
scale energy storage. In RFBs power and energy are decoupled: the former depends 
mainly on the size of the stack while the latter on the size tanks containing 
the redox active species. This feature makes RFBs ideal for economical, large-
scale energy storage. However, cost reduction is in order for allowing a 
widespread diffusion of this technology. Cell and stack design is a core task 
required for the development and upscaling of flow battery systems but redox 
flow cells models can be very complex due to the multitude of physical phenomena 
that need to be considered: electric fields, fluid flow, mass and specie 
transport in different components, electrochemical reactions, heat transfer. All 
these phenomena need to be considered to identify cell-limiting mechanisms, 
forecasting cell performance and optimizing the design.
 
We are looking for a motivated intern to support the development and validation 
of a multiphysics solver for redox flow battery simulations. The role involves 
working with an in-house existing solver based on OpenFOAM, testing it on 
various cell geometries, and conducting detailed post-processing. The intern 
will compare simulation results with experimental and literature data to enhance 
model accuracy and performance. This is a great opportunity to gain hands-on 
experience in CFD and multiphysics modeling and contribute to the advancement of 
energy storage technologies.

 
The following phases of work are expected:
-> Training and study of OpenFOAM: FVM implementation, code structure, solver 
structure
-> Analysis of different mathematical models used for modeling the different 
cells components (electrolytes, electrodes, membrane) and physical phenomena
-> Study and use of an existing library for modeling electrochemical systems
-> Preparing numerical analysis of redox flow batteries 
-> Creating CAD models for the testing purposes
-> Post-processing of simulation outcomes
-> Model validation based on experimental measurements 
-> The student will be supported by FBK’s researchers and the researcher will 
also guide the initial phases of training and the development of the activities.
 
Required qualification:
-> Enrolled in Master degree in Energy, Chemical or Mathematical Engineering, 
Physics/Chemistry or similar
-> Strong fundamentals of theory of fluid dynamics, thermodynamics, mass and 
heat transfer
-> Fundamentals of numerical methods and their applications, in particular 
Finite Volume Method (FVM)
-> Knowledge of general CFD concepts and workflows: pre-processing, runtime-
processing, post-processing, meshing, turbulence modelling, etc.
-> Fluency in one or more CAD softwares like: SolidWorks, Salome, FreeCad, 
Blender
-> Basic knowledge of electrochemistry / batteries
-> Practical experience in at least one programming language. Ideally C, C++ or 
Python
Ability to work in an international team;
-> Excellent problem-solving skills and attentions to details
-> Good level of English (both spoken and written)

Application have to be sent through the official job page. Other form of 
applications will not be considered.

Chiang Mai University (CMU) is offering 200 Graduate Level Full Scholarships per year, 
starting from the 1st Semester (June) of the 2019 academic year: 
an exciting opportunity to study at CMU for both Thai and foreign persons 
who possess a high potential and meet the requirements. 

Further info: https://drive.google.com/drive/folders/1St0enKmB3UZdJ44BqS5Ih0cBSC2YxN7H


Our Computational Turbulence and Aerodynamics Research Laboratory (CTAR) is 
looking for new master's students to join our lab.

Our research topics:
- Numerical Methods for fluid flows
- Multi-phase flow
- Geothermal Engergy
- Turbulence
- Acousitcs and vibration


Qualification: 
- Excellent skill in Mathematics, fundamental physics and programming ( Fortran, Python, MPI)
- Very driven personality and self-motivated.
 
The successful candidate will enjoy CMU's president's scholarship benefit and RA remuneration from our lab, which will match the scholarship amount.


More info:
CTAR Lab:   https://ctar-lab.org/ 
Mechanical Engineering Dept.:  https://me.eng.cmu.ac.th/
Alternative scholarship : https://grad-tara.oou.cmu.ac.th/?p=100&tab=5 

Chiang Mai University (CMU) is offering 200 Graduate Level Full Scholarships per year, 
starting from the 1st Semester (June) of the 2019 academic year: 
an exciting opportunity to study at CMU for both Thai and foreign persons 
who possess a high potential and who meet the requirements. 

Further info: https://drive.google.com/drive/folders/1St0enKmB3UZdJ44BqS5Ih0cBSC2YxN7H



Our Computational Turbulence and Aerodynamics Research Laboratory (CTAR) 
is looking for a new Ph.D. student to develop a very high-order multi-moment method which is a hybrid of FVM and FDM. 

Qualification:
- A very good background in CFD code development
- Excellent skill in Linux and programming ( Fortran, Python, MPI)
- Very driven personality and self-motivated.
 
The successful candidate will enjoy the CMU's president scholarship benefit 
as well as RA renumeration from our lab matching the scholarship amount.


More info:
CTAR Lab:   https://ctar-lab.org/ 
Mechanical Engineering Dept.:  https://me.eng.cmu.ac.th/
Alternative scholarship : https://grad-tara.oou.cmu.ac.th/?p=100&tab=5 

Papers to start from:
1. 10.1016/j.jcp.2005.08.002 
2. https://doi.org/10.1016/j.jcp.2020.109790 

Project Description

Scramjet engines are key enablers for hypersonic flight, promising efficient 
propulsion at speeds of Mach 5 and beyond. Yet the risk of unstart—where 
internal shock structures propagate upstream, choking the flow—threatens 
performance and stability. Prior studies have shown that unstart can be highly 
sensitive to small variations in pressure ratio and inlet boundary-layer 
profiles. Despite decades of investigation, many predictive tools lack robust 
ways to incorporate uncertainties in boundary conditions, turbulence modelling, 
and manufacturing variability.

Problem Statement

Conventional CFD workflows assume deterministic inputs, often using “best guess” 
values. These methods miss the probabilistic nature of input parameters, thereby 
underestimating unstart risks and limiting confidence in scramjet operability 
margins. Recent efforts integrated dimensionally adaptive sparse-grid techniques 
with RANS-based CFD, demonstrating that different probability distributions of 
uncertain parameters can drastically alter the predicted unstart risk. However, 
the published framework remains at a proof-of-concept stage, and broader 
application to realistic flight conditions requires further refinement.


Methods and Approaches

We will employ the open source JAX-Fluids solver to simulate flow within a 
representative isolator. This solver will be coupled with an uncertainty 
quantification toolkit based on adaptive sparse-grid sampling. Parameter 
distributions (e.g., pressure ratio, boundary-layer shape factor, turbulence 
modeling coefficients) will be derived from literature, experimental 
measurements, or expert elicitation. Each simulation’s outcomes—shock location, 
Mach-stem height, separation zones—will feed back into the UQ module to refine 
sampling in regions of high sensitivity.

Full advert and application: 

https://www.exeter.ac.uk/study/funding/award/?id=5526

PhD Project: Machine Learning Investigation of Unresolved Point Particles in Turbulent Flows (self-funded applicants)

The accurate representation of unresolved point particles remains a fundamental challenge in multiphase flow simulations. Traditional models often rely on empirical assumptions that limit predictive capabilities, especially in complex or turbulent environments. This PhD project aims to revolutionize particle-fluid interaction modeling by leveraging advanced machine learning techniques in CFD. By analyzing high-fidelity simulation data and experimental datasets, the project will develop data-driven models that can accurately predict particle forces, trajectories, and interaction dynamics within the fluid without relying solely on simplified closures.

The candidate will explore a range of machine learning approaches, including neural networks, ensemble methods, and physics-informed models, to capture hidden patterns in unresolved particle behavior. Emphasis will be placed on ensuring physical consistency, generalization across different flow regimes, and interpretability of the resulting models. Applications include environmental flows, industrial particulate processes, and biomedical systems where particulate transport is critical.

This project is based at Newcastle University, a prestigious institution ranked 129th in the world according to the QS World University Ranking. Newcastle offers access to excellent research facilities, a vibrant academic community, and a supportive environment for doctoral researchers.

Applicant Requirements

• Strong motivation for interdisciplinary research.
• Excellent analytical and problem-solving skills.
• Background in computational fluid dynamics (CFD) or related fields.
• Preferred: Experience with machine learning (ML) techniques.
• Preferred: Familiarity with programming languages such as Python, MATLAB, or C++.
• Good communication skills and ability to work both independently and as part of a team.

PhD Project: Machine Learning Investigation of Unresolved Point Particles in Turbulent Flows (self-funded applicants)

The accurate representation of unresolved point particles remains a fundamental challenge in multiphase flow simulations. Traditional models often rely on empirical assumptions that limit predictive capabilities, especially in complex or turbulent environments. This PhD project aims to revolutionize particle-fluid interaction modeling by leveraging advanced machine learning techniques in CFD. By analyzing high-fidelity simulation data and experimental datasets, the project will develop data-driven models that can accurately predict particle forces, trajectories, and interaction dynamics within the fluid without relying solely on simplified closures.

The candidate will explore a range of machine learning approaches, including neural networks, ensemble methods, and physics-informed models, to capture hidden patterns in unresolved particle behavior. Emphasis will be placed on ensuring physical consistency, generalization across different flow regimes, and interpretability of the resulting models. Applications include environmental flows, industrial particulate processes, and biomedical systems where particulate transport is critical.

This project is based at Newcastle University, a prestigious institution ranked 129th in the world according to the QS World University Ranking. Newcastle offers access to excellent research facilities, a vibrant academic community, and a supportive environment for doctoral researchers.

Applicant Requirements

• Strong motivation for interdisciplinary research.
• Excellent analytical and problem-solving skills.
• Background in computational fluid dynamics (CFD) or related fields.
• Preferred: Experience with machine learning (ML) techniques.
• Preferred: Familiarity with programming languages such as Python, MATLAB, or C++.
• Good communication skills and ability to work both independently and as part of a team.

Simerics Inc. is a global technology company that develops, markets, and 
supports Computer Aided Engineering (CAE) software widely used by OEMs and 
suppliers in various industries all over the world, with applications in 
automotive, hydraulics, marine and aerospace. The Simerics team is comprised of 
scientists and engineers who have been among the pioneers in the development and 
application of multipurpose computational physics since the early 1980s. This 
knowledge and experience are combined with new advances in computational 
physics, computational geometry, and software engineering to provide our clients 
with the next generation of simulation tools. Our team members are smart, 
motivated, friendly, and interesting people, most of whom hold a Ph.D.

Simerics Inc. offers two state-of-art general-purpose CFD tools: Simerics-MP and 
Simerics-MP+. Simerics-MP features a parallel solver that yields accurate and 
fast simulation for multi-purpose (MP) applications involving single-phase or 
multiphase flow, turbulence, cavitation/aeration, heat and mass transfer, 
particle and fluid-structure interaction. Simerics-MP+ includes all the 
capabilities of Simerics-MP with additional features such as streamlined setup 
procedures, automated mesh/re-mesh for key components especially moving 
components. 

With our continued expansion in the industry, we are currently seeking CFD 
project engineers to help meet the increasing demand in our Detroit office. The 
project engineer is responsible for providing expertise and developing CFD 
methods and will work closely with the customer and solver developers to 
communicate simulation results and recommendations. The candidate will use 
Simerics’ own software Simerics-MP/Simerics-MP+ to perform required simulations, 
in conjunction with Computer Aided Design (CAD) tools such as SolidWorks, PTC 
Creo, SpaceClaim, Python, and etc.

Detailed job responsibilities include:
CFD/CAE Applications:
• Develop 3D simulation models for various thermal/fluid applications including 
electric motor cooling for electric cars, battery cooling, fuel injection, oil 
splash in transmission gearbox, positive displacement pumps, valves, vehicle 
thermal management, and etc.
• Research and development of new methods and simulation processes to provide 
fast and accurate simulation strategy for customer’s product development.
• Analyze the dominant physics involved in the system (flow, multiphase, 
cavitation/aeration, pressure ripple, temperature, torque/power)
• Identify the critical parameters and perform optimization to improve product 
performance and design
• Interpret simulation results and prepare high-quality presentations.
• Participate in conferences and publish research articles.

Technical Training/Support:
• Provide modeling and simulation guidance and assistance to the users of 
Simerics, from pre-processing in CAD, simulation setup to post-processing.
• Training and interact with customers to analyze the technical needs, deliver 
reports and reviews, and provide solutions to clients’ technical challenges.
• Prepared and presented technical documents to show the features and 
capabilities of Simerics at conferences client meetings.

Required Qualifications:
• A Ph.D. degree in engineering, mathematics, physics or similar 
discipline with emphasis on thermal fluid. Or a master's degree with 1+ years 
equivalent industrial experience.
• Solid understanding of numerical methods, such as finite volume and finite 
difference methods.
• Strong technical background in fluid mechanics, heat transfer, thermodynamics.
• Highly motivated and dynamic, strong interpersonal and communication skills, 
be a team player
• Demonstrated skills in writing and presenting in fluent English
Desired Qualifications:
• Demonstrated experience programming in C, C++, FORTRAN, or Python.
• Familiarity with Linux and parallel computation.
• Experience with the use of commercial and/or non-commercial CFD tools in 
solving flow problems.
• Experience in multiphase flow, phase change.
• CAD experience (SolidWorks, Creo, CATIA, AutoCAD, or NX).
We sponsor H1-B working visa, but only the candidates in the US will be 
considered at this time. If interested, please send your CV to the hiring 
manager, Dr. Chiranth Srinvasan, at cs@simerics.com.

Simerics Inc. is a global technology company that develops, markets, and 
supports Computer Aided Engineering (CAE) software widely used by OEMs and 
suppliers in various industries all over the world, with applications in 
automotive, hydraulics, marine and aerospace. The Simerics team is comprised of 
scientists and engineers who have been among the pioneers in the development and 
application of multipurpose computational physics since the early 1980s. This 
knowledge and experience are combined with new advances in computational 
physics, computational geometry, and software engineering to provide our clients 
with the next generation of simulation tools. Our team members are smart, 
motivated, friendly, and interesting people, most of whom hold a Ph.D.

Simerics Inc. offers two state-of-art general-purpose CFD tools: Simerics-MP and 
Simerics-MP+. Simerics-MP features a parallel solver that yields accurate and 
fast simulation for multi-purpose (MP) applications involving single-phase or 
multiphase flow, turbulence, cavitation/aeration, heat and mass transfer, 
particle and fluid-structure interaction. Simerics-MP+ includes all the 
capabilities of Simerics-MP with additional features such as streamlined setup 
procedures, automated mesh/re-mesh for key components especially moving 
components. 

With our continued expansion in the industry, we are currently seeking CFD 
project engineers to help meet the increasing demand in our Detroit office. The 
project engineer is responsible for providing expertise and developing CFD 
methods and will work closely with the customer and solver developers to 
communicate simulation results and recommendations. The candidate will use 
Simerics’ own software Simerics-MP/Simerics-MP+ to perform required simulations, 
in conjunction with Computer Aided Design (CAD) tools such as SolidWorks, PTC 
Creo, SpaceClaim, Python, and etc.

Detailed job responsibilities include:
CFD/CAE Applications:
• Develop 3D simulation models for various thermal/fluid applications including 
electric motor cooling for electric cars, battery cooling, fuel injection, oil 
splash in transmission gearbox, positive displacement pumps, valves, vehicle 
thermal management, and etc.
• Research and development of new methods and simulation processes to provide 
fast and accurate simulation strategy for customer’s product development.
• Analyze the dominant physics involved in the system (flow, multiphase, 
cavitation/aeration, pressure ripple, temperature, torque/power)
• Identify the critical parameters and perform optimization to improve product 
performance and design
• Interpret simulation results and prepare high-quality presentations.
• Participate in conferences and publish research articles.

Technical Training/Support:
• Provide modeling and simulation guidance and assistance to the users of 
Simerics, from pre-processing in CAD, simulation setup to post-processing.
• Training and interact with customers to analyze the technical needs, deliver 
reports and reviews, and provide solutions to clients’ technical challenges.
• Prepared and presented technical documents to show the features and 
capabilities of Simerics at conferences client meetings.

Required Qualifications:
• A Ph.D. degree in engineering, mathematics, physics or similar discipline with 
emphasis on thermal fluid. Or a master's degree with 3+ years equivalent 
industrial experience.
• Solid understanding of numerical methods, such as finite volume and finite 
difference methods.
• Strong technical background in fluid mechanics, heat transfer, thermodynamics.
• Highly motivated and dynamic, strong interpersonal and communication skills, 
be a team player
• Demonstrated skills in writing and presenting in fluent English
Desired Qualifications:
• Demonstrated experience programming in C, C++, FORTRAN, or Python.
• Familiarity with Linux and parallel computation.
• Experience with the use of commercial and/or non-commercial CFD tools in 
solving flow problems.
• Experience in multiphase flow, phase change.
• CAD experience (SolidWorks, Creo, CATIA, AutoCAD, or NX).
We sponsor H1-B working visa, but only the candidates in the US will be 
considered at this time. If interested, please send your CV to the hiring 
manager, Dr. Chiranth Srinvasan, at cs@simerics.com.