6-month position for numerical simulation of dispersion and deposition of 
pollutants from chimneys over a residential area. The simulations will be 
carried out using Openfoam.
The period is from December 15 2017 to June 15 2018. 
The ideal candidate is familiar with Openfoam or with CFD simulations using 
commercial codes. Also, due to the limited time of the contract, the ideal 
candidate is from European Community, to avoid time delays associated with the 
visa procedure. The salary is 1500 EU after taxes per month, allowing a good 
quality of life in Trieste. Trieste is a beautiful Italian city over the 
Adriatic sea and the quality of life is excellent.
After this period, in case the recruited candidate exhibits excellence, a 
prolongation of the contract can be managed.  

6-month position for numerical simulation of dispersion and deposition of 
pollutants from chimneys over a residential area. The simulations will be 
carried out using Openfoam.
The period is from December 15 2017 to June 15 2018. 
The ideal candidate is familiar with Openfoam or with CFD simulations using 
commercial codes. Also, due to the limited time of the contract, the ideal 
candidate is from European Community, to avoid time delays associated with the 
visa procedure. The salary is 1500 EU after taxes per month, allowing a good 
quality of life in Trieste. Trieste is a beautiful Italian city over the 
Adriatic sea and the quality of life is excellent.
After this period, in case the recruited candidate exhibits excellence, a 
prolongation of the contract can be managed.  

Convergent Science Inc. specializes in modeling turbulent reacting flows using 
our CONVERGE™ CFD software. CONVERGE is loaded with state of the art physical 
models for turbulence, spray, conjugate heat transfer, fluid structure 
interaction, optimization and combustion.  CONVERGE is used by over 80% of the 
world’s internal combustion engine manufacturers.  Furthermore, adoption in 
other industries such as gas turbine combustion, pumps and compressors is 
growing rapidly.

Technical Account Manager

Convergent Science is looking for an ambitious technical account manager to help 
expand the usage of CONVERGE in Europe.   The position will require a self-
motivated individual eager to work with existing customers to maximize the value 
CONVERGE provides the organization.  Additionally, this individual will explore 
opportunities to introduce CONVERGE CFD software into new companies for a wide 
spectrum of applications (IC engine and non-IC engine). 
 
Client visits, sample problem solution, presentation creation, generation of 
marketing material, attending trade shows, conducting software training, 
providing technical sales support and negotiating licensing options will all be 
required on a regular basis.  
 
This position will be located in Linz, Austria.

Requirements:

+ Master’s degree or Ph.D. in Mechanical or Aerospace engineering or a related 
discipline
+ At least two years of training or work experience with computational fluid 
dynamics (CFD)
+ At least 2 years experience working with customers in a sales setting for CAE 
software.

Knowledge of any of the following applications is a plus:

+ internal combustion engine fundamentals
+ pumps
+ compressors
+ engine after-treatment (SCR/Urea) systems

 

We are in search of a motivated PhD student to join our group for Spring 2018 
(start date: January 2018) in pursuit of research in the following areas: 
turbulence modeling, artificial intelligence/machine learning, high 
performance computing with a possible application to massively separated 
turbulent flows. If interested, please send an email to Omer San 
(cfdlab.osu@gmail.com).

PS, students must first be admitted into the School of Mechanical and Aerospace 
Engineering (MAE)'s PhD degree program in order to be eligible to join our lab. 
Information on MAE graduate program admissions can be found 
https://mae.okstate.edu/content/graduate-program-admissions. 

Please see http://www.cfdlab.org/ for further details.


Overview: Turbulence models are a key tool in understanding complex flow 
physics in many applications. State-of-the-art turbulence models, however, are 
unlikely to enable high-fidelity predictions of massively separated flows due 
to the presence of an adverse pressure gradient, strong inhomogeneity and 
anisotropy. NASA has defined a technical challenge 
(https://turbmodels.larc.nasa.gov/nasa40percent.html) to identify and down-
select critical turbulence, transition, and numerical methodologies for a 40% 
reduction in predictive error against standard test cases for turbulent 
separated flows, evolution of free shear flows and shock-boundary layer 
interactions on state-of-the-art high performance computing hardware. In such a 
coarse-grained computational framework, the prediction of the free modeling 
parameters poses a grand challenge for the accurate modeling of turbulent flows 
with significant regions of separation. Therefore, the present project focuses 
on the discovery of radically new artificial intelligence approaches to model 
subgrid-scale physics of such complex phenomena. The overall goal of this 
project is thus to put forth a heuristics-free turbulence modeling framework, 
with the goal of developing robust and accurate closure models for the coarse-
grained simulations of flows in massively separated turbulent flow regimes.

We are in search of a motivated PhD student to join our group for Spring 2018 
(start date: January 2018) in pursuit of research in the following areas: 
turbulence modeling, artificial intelligence/machine learning, high 
performance computing with a possible application to massively separated 
turbulent flows. If interested, please send an email to Omer San 
(cfdlab.osu@gmail.com).

PS, students must first be admitted into the School of Mechanical and Aerospace 
Engineering (MAE)'s PhD degree program in order to be eligible to join our lab. 
Information on MAE graduate program admissions can be found 
https://mae.okstate.edu/content/graduate-program-admissions. 

Please see http://www.cfdlab.org/ for further details.


Overview: Turbulence models are a key tool in understanding complex flow 
physics in many applications. State-of-the-art turbulence models, however, are 
unlikely to enable high-fidelity predictions of massively separated flows due 
to the presence of an adverse pressure gradient, strong inhomogeneity and 
anisotropy. NASA has defined a technical challenge 
(https://turbmodels.larc.nasa.gov/nasa40percent.html) to identify and down-
select critical turbulence, transition, and numerical methodologies for a 40% 
reduction in predictive error against standard test cases for turbulent 
separated flows, evolution of free shear flows and shock-boundary layer 
interactions on state-of-the-art high performance computing hardware. In such a 
coarse-grained computational framework, the prediction of the free modeling 
parameters poses a grand challenge for the accurate modeling of turbulent flows 
with significant regions of separation. Therefore, the present project focuses 
on the discovery of radically new artificial intelligence approaches to model 
subgrid-scale physics of such complex phenomena. The overall goal of this 
project is thus to put forth a heuristics-free turbulence modeling framework, 
with the goal of developing robust and accurate closure models for the coarse-
grained simulations of flows in massively separated turbulent flow regimes.







 

Start date : 1st April 2018 (flexible)

Project duration : 1 year

Funding agency : EPSRC

Job description:

You will contribute to a project titled “UNSflow: A low-order, open-source solver for problems that involve 
unsteady and nonlinear fluid dynamics,” working with Dr. Kiran Ramesh (PI). Specifically, the job requires 
expert knowledge in unsteady aerodynamics and computational modelling. The successful candidate will also 
be expected to contribute to the formulation and submission of research publications and research proposals 
as well as help manage and direct this complex and challenging project as opportunities allow.

Project description:

This project aims to derive and develop new theoretical and low-cost numerical methods (from potential flow 
and boundary layer theories) for analysing general unsteady aerofoil and wing flows that may exhibit 
nonlinearities such as flow separation and vortex shedding. The solvers implemented through these methods 
will be made available (open-source) to the public, academia and industry through the UNSflow project. 
https://github.com/KiranUofG/UNSflow

The research to be carried out in this project is fundamental in nature and underpins several applied 
problems. It will assist the principal investigator’s research group in its research on applied problems such as 
aerodynamic optimisation, dynamic stall alleviation, flapping-wing design and wind-energy harvesting. 

To discuss the project further, get in touch : kiran.ramesh@glasgow.ac.uk

To apply : https://www.gla.ac.uk/it/iframe/jobs/ 
Ref 019214

The Fluid Mechanics Laboratory at Columbia University, opening on January 1st 2018 as part of the Civil 
Engineering and Engineering Mechanics Department, is seeking applications for two Ph.D. positions in 
computational and theoretical fluid mechanics.

The principal objective of the Fluid Mechanics Laboratory will be to advance the physical understanding of 
turbulence and related non-linear multi-scale phenomena. These advances are directed to improving 
capabilities for modeling and control of turbulence in engineering and environmental applications. The ideal 
candidate should have a background in Engineering, Physics, Mathematics, Computational Science, or a 
related field, be passionate about fluid mechanics, and have strong numerical and analytical skills. The 
candidate will pursue leading-edge research on selected topics including turbulent transport in boundary-
layer flows, turbulence modeling, high Reynolds number canopy flows (e.g. flows over urban environments), 
and work on the development of numerical and analytical methods for the description of fluid motions. 
The Ph.D. thesis will be developed at Columbia University in the city of New York, and collaboration will be 
fostered with colleagues from world-leading institutions. A competitive salary including tuition fees and full 
employee benefits are offered in accordance with the University guidelines.

The interested applicant should send a Curriculum Vitae and a cover letter describing his/her areas of 
expertise and interest at mg3929@columbia.edu, along with names and contact information of one to two 
references. Feel free to contact me directly at the address above should more information be needed. The 
review process will commence immediately and continue until positions are filled.

Sincerely,

Marco Giometto,
Assistant Professor at Columbia University 
Department of Civil Engineering and Engineering Mechanics 

The chair of “Numerical Fluid and Gasdynamics” has 
to fill asap a 3 year postdoc position in the field of computational fluid
dynamics. 

Area of research

The group's research focuses on stochastic low order modelling approaches for
turbulent flow. Currently approaches like LEM, ODT, HIPS, ODTLES, and XLES are investigated and
applied to interdisciplinary problems in fluid dynamics. While LEM, HIPS, and ODT are pure
one-dimensional approaches and thus only yield statistics on a line of sight through the flow field, XLES,
where X stands for LEM/HIPS/ODT are multi-dimensional approaches and are able to generate
structural information like DNS or highly resolved LES. Applications of these very efficient 
models can be  multidisciplinary, e.g. combustion, meteorology, and canonical
flows. The postdoc might chose his preferred research direction. 

The challenge

We want to extend the aforementioned methods to an efficient
deterministic/stochastic multi-scale approach to investigate turbulent flows.
Especially, we want to know what kind of scales might be computed with a low order stochastic approach and 
which ones should be fully 3D resolved like in DNS to capture the correct flow dynamics. 

Your profile

We are looking for a talented individual who is excited about research and
interested in pursuing an academic career. The candidate should be able to work
independently as well as to cooperate in an interdisciplinary team of
researchers. Applicants should hold a recent PhD degree (not older than 6 years)
in CFD, computational engineering/physics, applied mathematics, or a closely related
field. The project will involve the numerical solution and analysis of
turbulent flows using different codes developed at the chair.
The candidate should have a solid background in fluid mechanics and numerical
methods. Very good programming skills in e.g. Fortran/C/C++ are required as well as experience in
parallel computing. Experience with stochastic modelling or DNS would be perfect. Good communication 
skills and fluency in both written and spoken English are required. German language skills (B1 or better) are
necessary since the position includes teaching duties. Latter are in the field of gasdynamics and numerical
methods.

Our offer 

The Brandenburg Technical University BTU Cottbus-Senftenberg offers excellent
working conditions in a highly international research environment. The salary is in accordance to the
Public Sector Collective Agreement on Länder (TV-L). The wage classification will be carried out after
presenting the personal requirements as pay grade TV-L E 14. This salary is awarded as the candidate
will also have teaching and administrative duties. The candidate should also be able to co-supervise some of
the group's Ph.D. students. The position can be filled asap but latest from February 2018 and is limited to
three years. Prolongation via third party funding might be possible and depends on the candidate's 
performance.

Your application

Please send your application only by electronic mail and preferably in one
single pdf-document to heischmi@zedat.fu-berlin.de. Applications will be processed as soon as they are
received. For full consideration, the application should include a cover letter, a
detailed CV, a list of publications, copies of all educational certificates and transcripts of records, a summary 
of past research activities, evidence of teaching interest and abilities, and at least two letters of
recommendation.

We are now searching for motivated students to pursue research in one of the
following areas:

    Modeling of multicomponent mixtures of supercritical fluids
    Developing advanced bioprinting technologies
    Exploring pilot-wave dynamics, the quantum mechanics analogue in fluid mechanics

One research assistantship ($18,000 per year and waiver of tuition) for a
doctoral student is available. Computational programming experience in C/C++ or
Fortran is preferred. If interested, please send an email to phe@lamar.edu with
your CV, transcripts and 2-3 reference contacts.

dm-airtechs are consulting engineers in the process of expanding their services. 

Originally, we have started our business because despite the huge number of consulting engineers 
out there we knew that our passion for CFD, aeroelasticity and computational physics would have 
done the difference.
Motivated by that never ending passion and strengthened by the positive feedbacks, we are going 
on challenging ourselves and solving every single problem.

We are now looking for passioned and prepared:

- CFD engineering. OpenFoam, mesh preparation are must as well as the understanding of Fluid 
Mechanics.

- Software Engineer. C++ and software development are required.

We also accept highly motivated students that are willing to deploy their passion and their fresh view 
on the problem. Since we are overwhelmed by an huge amount of work, only the most interesting 
contacts will be considered.