Organisation/Company Polytechnic University of Bari Research Field Engineering » Aerospace engineering Engineering » Mechanical engineering Engineering » Simulation engineering Physics » Applied physics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 31 Dec 2026 - 23:59 (Europe/Rome) Country Italy Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Is the Job related to staff position within a Research Infrastructure? No

Offer Description
About HyNOISE

HyNOISE is a Doctoral Network aimed to train doctoral candidates able to face current and future challenges in the prediction and control of direct and indirect noise generated by hydrogen flames. Four specific research objectives will be pursued: 1) Unveil the dynamics and sound pressure level generated during unsteady ignition and flashback process 2) Investigate the direct broadband sound generated due to the coupling between unsteady flame dynamics and flame-flame interactions, hydrodynamic and thermo- diffusive instabilities, and turbulence. 3) Understand physical mechanisms leading to the onset of thermoacoustic instabilities coupled with different modes at either with a specific focus on high frequencies 4) Study the contribution of convective waves to combustion noise and thermoacoustic instabilities. Multiple hydrogen-air archetypes typical of air-breathing hydrogen combustion systems in both single and annular multi-injector configurations will be investigated. In a collaborative partnership between academic and industry partners who are major European gas turbine manufacturers, HyNOISE bring relevant expertise together and to pursue solutions for hydrogen through integration and combination of unique and advanced theoretical, high-fidelity modelling and experimental expertise. This will lead to the development of new models and tools able to correctly predict hydrogen flame dynamics and its resulting pressure field, and, on this basis, developing control and mitigation methods to overcome current limitations in hydrogen combustion systems and design innovative, quiet, and stable combustion devices. The technologies developed will stimulate the green transition in the power generation and transport sectors, thus contributing to the achievement of the EU's challenging decarbonization goals.

About the host organization

Technische Universität Berlin (TUB) is one of the largest technical universities in Germany. Its seven faculties cover engineering and natural sciences, economics and business, planning sciences, humanities and the social sciences. The TUB has a professional EC Funding Support Service with long-standing experience in the administration of EC grants (FP 7: 211 contracts, Horizon 2020: 160 contracts and Horizon Europe: 103 contracts so far). The TU Berlin received approx. 138 million € funding (Horizon 2020 & Horizon Europe). The Institute of Fluid Dynamics and Technical Acoustics (ISTA) within the Department of Mechanical Engineering and Transport Systems performs teaching and research related to fluid dynamics, acoustics, and combustion. The Chair of Fluid Dynamics (Prof. C. Oliver Paschereit, website: https://www.tu.berlin/fd ) and the Laboratory for Flow Instability and Dynamics (Dr. Thomas Kaiser https://www.tu.berlin/index.php?id=34633 ) at the ISTA at the ISTA closely collaborate on research and development in experimental combustion and fluid dynamics and their modelling. Beside fundamental research, development work is being performed for major companies in power generation as well as in transportation.

Individual Research Project (IRP)

Title: Identification and modelling of hydrodynamic instabilities driving combustion noise in turbulent hydrogen flames

The main objective of the project is to identify the key mechanisms that drive combustion noise in turbulent hydrogen jet flames and to develop a physics-based, low-order modelling framework that can be used to optimize combustion systems. The focus will be on direct combustion noise of circular turbulent non-swirling jet flames caused by the dynamic interaction of turbulent structures of the underlying flow field and the flame front. To construct a comprehensive database, we execute compressible reacting Large Eddy Simulations, mirroring TUB’s experiments. Using extended Spectral Proper Orthogonal Decomposition,



we derive low-order dynamical models revealing dominant flow structures and their interaction with flame dynamics and noise. These insights inform a physics-grounded model of said structures, employing the linearized Navier-Stokes equations using an active flame approach. Addressing turbulence closure, we pioneer a data assimilation method employing physics-informed neural networks (PINNs). As next step, we employ the resolvent framework to estimate direct noise from the linearized model and compare with acoustic measurements conducted at TUB. For quantitative comparison, a low order model of the resolvent forcing will be developed. The model is then used in a parametric study to probe how diverse combustion conditions (i.e., Reynolds number, equivalence ratio, preheat temperature) affect noise. The PINN-based assimilation process obviates LES reruns by directly integrating experimentally determined mean fields. Through these efforts, we aim to untangle combustion noise intricacies, advancing combustion system design and operation.

Research Objectives

Compressible LES of hydrogen jet flame.
Empirical modelling using extended SPOD and clustering.
Assimilation of closure models of linearized reacting field equations using PINNs.
Resolvent analysis based on assimilated linearized mean field equations and comparison with empirical modes and noise.
Investigation and low order modelling of optimal forcing modes for quantitative noise prediction.
Parametric study to investigate the influencing parameters on flame noise

Expected Results

Compressible LES of a turbulent hydrogen jet flame for experimental validation.
SPOD-based identification of turbulent structures driving combustion noise.
Linearized framework to model these mechanisms for optimization studies.

Secondments

Politecnico di Bari (Italy, ca. 3 months): apply developed linearized model for noise estimation of LES dataset from DC9
University of Cambridge (UK, ca. 2 months): improving LOM modelling using data-driven approached developed by DC12

The IRP will have a strong link to other IRPs from different DCs for:

Work on joint simulation and modelling
Provision of input and data

Where to apply
E-mail [email protected]

Requirements
Research Field Engineering » Mechanical engineering Education Level Master Degree or equivalent

Research Field Engineering » Aerospace engineering Education Level Master Degree or equivalent

Research Field Physics » Applied physics Education Level Master Degree or equivalent

Skills/Qualifications

Essential skills and requirements

MSc or equivalent in the field of aerospace engineering, mechanical engineering, physics or similar
Solid knowledge of fluid mechanics, thermodynamics, numerical methods and computational fluid dynamics (CFD).
Strong analytical skills and an interest in combining high-fidelity numerical simulations with physics-based reduced-order modelling .
Ability to work both independently and collaboratively in an interdisciplinary and international research environment.
Ability to solve complex problems with adherence of strict deadlines
Excellent communication skills (both written and verbal) in English to derive the full vantaggi from the network training
As secondmentsand events are foreseen, applicants must be ready to travel
Applicants must meet the formal requirements for admission to doctoral studies at Technische Universität Berlin

Desired skills

Experience with turbulent or reacting-flow simulations is highly desirable.
Good programming skills, preferably in Python, C/C++ or a comparable scientific programming language .
Experience with Linux and high-performance computing is desirable.
Knowledge of turbulence, combustion, acoustics, or thermoacoustics is advantageous.
Experience with data-analysis or reduced-order modelling techniques such as POD/SPOD, resolvent analysis, system identification or machine learning is advantageous, but not required.

Specific Requirements





Applicants can be of any nationality.
Candidates may apply prior to obtaining their master’s degree, but cannot receive an employment contract before having obtained the master degree.
Candidates may apply to multiple positions offered within HyNOISE, but should carefully choose the ones that they apply for.

In addition:

Horizon Europe MSCA Mobility Rule: Researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of the host organization (Germany) for more than 12 months in the 36 months immediately before the recruitment date – unless as part of a compulsory national service or a procedure for obtaining refugee status under the Geneva Convention.

Horizon Europe MSCA Eligibility Criteria: Doctoral Candidates (DC) must, at the date of recruitment by the host organization, have not been awarded a doctoral degree.

Applicants who do not fulfill the Mobility Rule and the Eligibility Criteria CANNOT be considered for the research position.

Languages ENGLISH Level Excellent

Additional Information
You will be working within our international group of researchers with experience in a broad range of sciences.
You will get in contact with the other members of this international consortium.
You will benefit from the well-structured training program offered by the host institution and the HyNOISE consortium to develop skills and thorough understanding of space transportation systems and their environmental impact.
You will be employed by the host organization for 36 months.
You will participate in international conferences and secondments to other organizations within the HyNOISE network and in outreach activities targeted at a wide audience.
Employment and remuneration at TU Berlin will be in accordance with the applicable TV-L collective agreement. The MSCA fundings (see page 118ff.) includes a living allowance, a mobility allowance and, where applicable, a family allowance; where the applicable MSCA allowances exceed the corresponding TV-L remuneration, the fellow will receive the full eligible allowance amounts.

Please find additional information in the Information package for Marie Curie fellows in Doctoral Networks referenced in the original listing.

Selection process

Selection process

For the selection procedure, the HyNOISE consortium will appoint a Recruitment Committee (RC) for each position. The selection will be carried out in two consecutive stages. In the primary selection, the RC evaluates all submitted application documents. Eligible candidates of sufficient quality will be shortlisted. In the final selection, short-listed applicants are invited to interviews, held either in person at the host institution or via video-conference, and to complete a position-specific task. Both interviews and tasks are evaluated against predefined criteria, leading to a ranked list of candidates. Final decisions are made by consensus within the RC. Applicants will be informed about rejection or admission to the interview stage by the end of January 2027. The employment and relocation phase will then start immediately, allowing sufficient time for contracting, visa applications, and relocation before the official start of the DC projects by October 2027.

Expected starting date: January - October 2027

Applications and enclosures received after the deadline will not be considered.

More information and other vacant positions can be found at:

Reference to data protection: The personal data you submit will be processed at POLIBA in accordance with its Data Protection Declaration ( https://www.poliba.it/en/protezione-dei-dati-personali ). In addition, your personal data will be shared with the consortium partners (see https://cordis.europa.eu/project/id/101311721 ) for the purpose of evaluating your application and carrying out the joint selection procedure. The project partners are joint responsible for the processing of personal data.

We in the HyNOISE consortium value diversity and we commit to equal treatment of all applicants irrespective of gender, sexuality, health status as well as social, cultural or religious background.

Number of offers available 1 Company/Institute Technische Universität Berlin (TUB), Institute of Fluid Dynamics and Technical Acoustics (ISTA) Country Germany State/Province Germany City Berlin Postal Code 10623 Street Müller-Breslau-Str. 8 Geofield

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📌 PhD student – HyNOISE Doctoral Candidate: Identification and modelling of hydrodynamic instab (Roma)
🏢 Polytechnic University Of Bari
📍 Roma