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[Sponsors] |
Job Record #19663 | |
Title | Advanced CFD Engineer - Ceramic Injection Moulding IGT |
Category | Job in Industry |
Employer | University of Leeds/Morvern Group Ltd. |
Location | United Kingdom |
International | Yes, international applications are welcome |
Closure Date | Monday, May 05, 2025 |
Description: | |
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 |
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Contact Information: | |
Please mention the CFD Jobs Database, record #19663 when responding to this ad. | |
Name | Dr Zinedine Khatir |
Z.Khatir@leeds.ac.uk | |
Email Application | No |
URL | https://www.jobs.ac.uk/job/DMS266/ktp-associate-advanced-computational-fluid-dynamics-for-ceramic-injection-moulding-turbine-aerofoils-casting-industry |
Record Data: | |
Last Modified | 18:27:44, Wednesday, April 30, 2025 |
Job Record #19662 | |
Title | Master thesis on flow batteries OpenFOAM model validation |
Category | Internship |
Employer | Fondazione Bruno Kessler |
Location | Italy, Trentino - Alto Adige, Trento |
International | Yes, international applications are welcome |
Closure Date | * None * |
Description: | |
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. |
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Contact Information: | |
Please mention the CFD Jobs Database, record #19662 when responding to this ad. | |
Name | Maciej Marczak |
mmarczak@fbk.eu | |
Email Application | Yes |
Phone | 3286985159 |
URL | https://jobs.fbk.eu/Annunci/Jobs_Internship_master_thesis_on_batteries_Development_and_validation_of_multiphysics_models_for_redox_flow_batteries_226177138.htm |
Record Data: | |
Last Modified | 16:31:14, Wednesday, April 30, 2025 |
Job Record #19661 | |
Title | Chiang Mai President Scholarship for Master's Study |
Category | PhD Studentship |
Employer | Chiang Mai University |
Location | Thailand, Chiang Mai |
International | Yes, international applications are welcome |
Closure Date | * None * |
Description: | |
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 |
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Contact Information: | |
Please mention the CFD Jobs Database, record #19661 when responding to this ad. | |
Name | Arpiruk Hokpunna |
arpiruk.hok@eng.cmu.ac.th | |
Email Application | Yes |
URL | http://ctar-lab.org |
Record Data: | |
Last Modified | 23:11:23, Tuesday, April 29, 2025 |
Job Record #19660 | |
Title | Ph.D. in Multi-Moment Method |
Category | PhD Studentship |
Employer | Chiang Mai University |
Location | Thailand, Chiang Mai |
International | Yes, international applications are welcome |
Closure Date | Friday, May 30, 2025 |
Description: | |
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 |
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Contact Information: | |
Please mention the CFD Jobs Database, record #19660 when responding to this ad. | |
Name | Arpiruk Hokpunna |
arpiruk.hok@eng.cmu.ac.th | |
Email Application | Yes |
URL | http://ctar-lab.org |
Address | arpiruk.hok@eng.cmu.ac.th |
Record Data: | |
Last Modified | 23:10:05, Tuesday, April 29, 2025 |
Job Record #19659 | |
Title | CFD Engineer – OpenFOAM/Ansys Simulations |
Category | Job in Academia |
Employer | IIT Delhi |
Location | India, Delhi, New Delhi |
International | No, only national applications will be considered |
Closure Date | Thursday, May 15, 2025 |
Description: | |
We are seeking a motivated CFD Engineer with expertise in OpenFOAM/Ansys to perform large-scale multiphase RANS/LES/DES simulations for advanced research in turbulent flow and drag reduction strategies. The selected candidate will work on simulating multiphase turbulent flows involving air injection through surface holes and study the effects of various control parameters on near-wall turbulence characteristics. Extensive RANS/LES/DES simulations have to be conducted using OpenFOAM/Ansys to investigate multiphase turbulent flows. Analyze the impact of control parameters such as: Reynolds number Streamwise location of air injection Weber number and Froude number Bubble diameter relative to the Kolmogorov length scale Bubble void fraction and distribution Slip length for Superhydrophobic Surfaces (SHS) and trapped air characteristics ________________________________________ Required Skills: • Strong expertise in OpenFOAM or similar open-source CFD solvers. • Solid understanding of RANS/LES/DES modeling, multiphase flows, and turbulence physics. • Proficiency in Eulerian–Lagrangian multiphase modeling. • Knowledge of bubble dynamics and drag reduction mechanisms. • Good programming/scripting skills (C++, Python, or Bash scripting preferred). • Experience in post-processing tools such as ParaView. | |
Contact Information: | |
Please mention the CFD Jobs Database, record #19659 when responding to this ad. | |
Name | Vamsi Chalamalla |
vchalama@am.iitd.ac.in | |
Email Application | Yes |
Record Data: | |
Last Modified | 20:36:32, Monday, April 28, 2025 |
Job Record #19658 | |
Title | HYPER-UQ: Hypersonic Prediction & Risk Evaluation |
Category | PhD Studentship |
Employer | Dept Engineering, University of Exeter |
Location | United Kingdom, Devon, Exeter |
International | Yes, international applications are welcome |
Closure Date | Thursday, May 15, 2025 |
Description: | |
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 |
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Contact Information: | |
Please mention the CFD Jobs Database, record #19658 when responding to this ad. | |
Name | Dr Xu Chu |
x.chu@exeter.ac.uk | |
Email Application | Yes |
URL | https://www.exeter.ac.uk/study/funding/award/?id=5526 |
Record Data: | |
Last Modified | 15:59:23, Monday, April 28, 2025 |
Job Record #19656 | |
Title | Machine Learning for CFD of Point Particles (self-funded) |
Category | Job in Academia |
Employer | Newcastle University |
Location | United Kingdom, Newcastle upon Tyne |
International | Yes, international applications are welcome |
Closure Date | Thursday, April 30, 2026 |
Description: | |
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
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Contact Information: | |
Please mention the CFD Jobs Database, record #19656 when responding to this ad. | |
Name | Dr. Amir Fard |
amir.fard@newcastle.ac.uk | |
Email Application | Yes |
URL | https://www.ncl.ac.uk/engineering/staff/profile/amirfard.html |
Record Data: | |
Last Modified | 22:04:34, Saturday, April 26, 2025 |
Job Record #19657 | |
Title | Machine Learning for CFD of Point Particles (self-funded) |
Category | PhD Studentship |
Employer | Newcastle University |
Location | United Kingdom, Newcastle upon Tyne |
International | Yes, international applications are welcome |
Closure Date | Sunday, May 31, 2026 |
Description: | |
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
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Contact Information: | |
Please mention the CFD Jobs Database, record #19657 when responding to this ad. | |
Name | Dr. Amir Fard |
amir.fard@newcastle.ac.uk | |
Email Application | Yes |
URL | https://www.ncl.ac.uk/engineering/staff/profile/amirfard.html |
Record Data: | |
Last Modified | 22:03:31, Saturday, April 26, 2025 |
Job Record #19375 | |
Title | CFD Intern |
Category | Job in Industry |
Employer | Simerics, Inc. |
Location | United States, Michigan, Novi |
International | No, only national applications will be considered |
Closure Date | * None * |
Description: | |
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. |
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Contact Information: | |
Please mention the CFD Jobs Database, record #19375 when responding to this ad. | |
Name | Chiranth Srinivasan |
cs@simerics.com | |
Email Application | Yes |
URL | http://www.simerics.com |
Record Data: | |
Last Modified | 19:57:13, Thursday, April 24, 2025 |
Job Record #19107 | |
Title | Project Engineer |
Category | Job in Industry |
Employer | Simerics, Inc. |
Location | United States, Michigan, Novi |
International | No, only national applications will be considered |
Closure Date | * None * |
Description: | |
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. |
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Contact Information: | |
Please mention the CFD Jobs Database, record #19107 when responding to this ad. | |
Name | CHIRANTH SRINIVSAN |
cs@simerics.com | |
Email Application | Yes |
Phone | 4053089420 |
URL | http://www.simerics.com |
Record Data: | |
Last Modified | 19:56:36, Thursday, April 24, 2025 |