30 October 2026
Job Information
- Organisation/Company: Polytechnic University of Bari
- Research Field: Engineering » Aerospace engineering; Engineering » Mechanical engineering; Engineering » Simulation engineering; Physics » Applied physics
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
University of Cambridge (UCAM) is one of the leading scientific research institutions worldwide and is regularly ranked in the top 5 universities. The Engineering Department is the highest-ranking department of its type in the UK. It is an integrated department, with several cross-disciplinary collaborations. The department has 180 members of staff, 700 post-doctoral researchers and a similar number of graduate students. A sizable fraction of the activity, involving 70 staff in the university, revolves around fluid mechanics, aeroacoustics and combustion, with a correspondingly large number of PhD students.
Individual Research Project (IRP)
Problem Definition
The overall objective is to optimize the design of hydrogen-fuelled gas turbine injectors, so that the combustors are quiet and not susceptible to thermoacoustic instabilities. This requires a quantitatively accurate model of the thermoacoustic system, which is the combination of a hydrogen flame with an acoustic network. This model will be obtained by systematic assimilation of data from laboratory experiments (NTNU), large eddy simulations (TUB), and industrial experiments (RRD). This data will be assimilated into thermoacoustic models using UCAM’s adjoint-accelerated inference and optimization method (AXIOM). The first intermediate objective is to extend AXIOM to typical hydrogen flame geometries using data from a laboratory scale combustor at NTNU. Bayesian model selection (a component of AXIOM) will be used to find the optimal component models for this simple system. The second intermediate objective is to extend AXIOM to industrial scale geometries using data from a real gas turbine fuel injector on an industrial test rig at RRD. Bayesian experimental design (another component of AXIOM) will be used to identify the experimental configurations that maximize the information that can be learned from a limited number of tests. The third intermediate objective is to develop and test several candidates mean field flame models with TUB and then to assimilate LES data into these models with AXIOM. This is an ambitious objective, but the risk it generates is mitigated by TUB’s use of PINNs to achieve the same objective. The result will be a Bayesian framework that transfers data from experiments and numerical simulations into low order models. These models will steadily accumulate data and become more quantitatively accurate over time. They can therefore be used for optimization and re-optimization, as more data become available in the future and as future designs change.
Research Objectives
- Assimilation of experimental data from laboratory scale combustor into thermoacoustic models and flame models.
- Assimilation of experimental data from RRD industrial scale test rig into thermoacoustic models.
- Development and testing of several candidate mean field flame models with TUB.
- Assimilation of LES data into candidate mean field flame models and identification of optimal models.
- Assimilation of experimental data from RRD industrial scale test rig into flame models.
- Optimization of burner design to reduce susceptibility to thermoacoustic instability
Expected Results
- Detailed description of the acoustic field in premixed hydrogen combustion in canonical configurations.
- Creation of a quantitatively accurate thermoacoustic model of the RRD industrial scale test rig containing an industrial burner, able to match experimental results from the RRD rig within quantified uncertainty bounds and able to extrapolate to different configurations within predicted uncertainty bounds.
- Creation of a quantitatively accurate mean field flame model of a turbulent hydrogen flame, able to match the LES results on which it was trained to within quantified uncertainty bounds, and able to extrapolate to unseen LES data.
- Optimal burner design derived from the quantitatively accurate models obtained from outcomes 1 & 2, and a numerical tool for optimizing the design at different conditions and combustor geometries.
Secondments
- Technical University of Berlin (Germany, ca. 2 months): application of developed model to improve mean fields reconstructions of non-measured quantities
- ETH Zurich (Switzerland, ca. 2 months): to check capabilities of LOM to predict indirect noise
The IRP will have a strong link to other IRPs from different DCs for:
- Work on joint modelling and simulations
- Provision of input and data
Where to apply
E-mail: hynoise-dn@poliba.it
Requirements
- Research Field: Engineering » Aerospace engineering
Education Level: Master Degree or equivalent - Research Field: Engineering » Mechanical 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 on Fluid Mechanics and Thermodynamics, Computer Science and Informatics (Numerical Analysis; simulation, optimisation and modelling tools; Computational Fluid Dynamics (CFD))
- Ability to work efficiently and self-reliantly in a diverse inter-disciplinary and multi-cultural environment
- Ability to work in a team as well as independently
- Ability to solve complex problems with adherence of strict deadlines
- Proactive attitude
- Excellent communication skills (both written and verbal) in English to derive the full benefit from the network training
- As secondments and events are foreseen, applicants must be ready to travel
Specific Requirements
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 (United Kingdom) 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
Benefits
Benefits
- 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.
- A competitive salary according to MSCA regulations (see page 118ff.), including a living allowance, a mobility allowance and, if eligible, a family allowance. The stated allowances represent the gross funding amounts. Employer contributions to social security, health insurance, and other statutory costs will be deducted in accordance with the applicable national regulations.
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.
Additional comments
Application
Interested candidates are invited to submit one single PDF containing the following documents in this exact order:
- Cover letter
- An evidence-based CV that reflects a representative array of achievements and qualifications appropriate to the position you are applying for
- Reference letters or, at minimum, the contact details of persons that may be contacted for reference
- Educational and professional certificates (university degree(s) with marks, internships, workshops, languages, etc.)
All the application documents must be submitted via email to hynoise-dn@poliba.it
The email subject must be “Application for DC12 position”.
The email size incl. attachments must not exceed 30 MB in total.
Candidates whose application is not compliant with the requirements above will not be considered.
Application deadline: 31 December 2026 at 11:59 PM CEST
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.
For additional information about the research project and this individual position, please contact: hynoise-dn@poliba.it or the main supervisor (mpj1001@cam.ac.uk).
Work Location(s)
- Number of offers available: 1
- Company/Institute: University of Cambridge, Engineering Department
- Country: United Kingdom
- State/Province: United Kingdom
- City: Cambridge
- Postal Code: CB2 1PZ
- Street: Trumpington Street
Contact
- City: Bari
- Website: https://www.linkedin.com/company/hynoise-dn/
- Street: Giovanni Amendola, 126/b
- Postal Code: 70126
- E-Mail: hynoise-dn@poliba.it