PhD student – HyNOISE Doctoral Candidate: A systematic assimilation data model to predict thermoacoustic instabilities
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
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)
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
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 fulfil 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 vantaggi 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
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.
More information and other vacant positions can be found at:
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 Geofield
#J-18808-Ljbffr
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)
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
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 fulfil 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 vantaggi 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
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.
More information and other vacant positions can be found at:
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 Geofield
#J-18808-Ljbffr