Post-Doctoral Researcher: Scientific Software Development and Machine Learning for Thermal Industrial Systems

Technological University Dublin; Ireland; On-site; EUR 42,000 - 60,000; Full time

Job summary

Technological University Dublin’s TFES Research Group invites applications for a postdoctoral researcher focused on software engineering for thermal systems modelling. You will implement numerical methods and ML models in code, develop surrogate models, and integrate them into a broader software platform, with validation against experimental data.

The role emphasises software development, collaboration with industry partners, and dissemination through publications and conferences.

Qualifications

• PhD or equivalent in mechanical, thermal, energy or aerospace engineering, applied mathematics, physics, CS, scientific computing or closely related discipline.
• Evidence of a strong research profile and publication record in the subject area.
• Experience with research techniques and methodologies.
• Demonstrated ability to develop and maintain research software with clear contribution details.
• Experience implementing numerical methods or ML models in Python with scientific stack.
• Experience with software engineering practices in a research context (Git, modular code, testing, documentation).
• Working knowledge of heat transfer, fluid mechanics or thermodynamics for physics-based model calibration and validation.
• Excellent written and verbal communication skills with ability to present to academic/industry audiences.

Responsibilities

• Lead the technical delivery of modelling and software work for a defined package.
• Implement numerical methods and machine learning models in code.
• Develop reduced-order and hybrid surrogate models with real-time performance and error bounds.
• Define modelling standards and input/output conventions; automate model generation and packaging.
• Integrate models into a wider software platform and validate against data; coordinate with external collaborators.

Skills

Python programming

Research software development

Git version control

Technical documentation

Academic communication

Numerical methods

Machine learning for engineering

Publications track record

Industry collaboration

Education

PhD in mechanical/thermal/energy/aerospace engineering or related

Tools

NumPy/SciPy/pandas

PyTorch/TensorFlow/Scikit-learn

Git

Containerization (Docker)

Job description

Directorate of Research, Enterprise & Innovation Services

Organisation/Company Technological University Dublin Department Directorate of Research, Enterprise & Innovation Services Research Field Engineering » Mechanical engineering Physics Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions Application Deadline 5 Oct 2026 - 17:00 (Europe/Dublin) Country Ireland Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? European Union / Next Generation EU Is the Job related to staff position within a Research Infrastructure? Yes

Offer Description

Function

The Thermo-Fluids and Energy Systems (TFES) Research Group in the School of Mechanical Engineering carries out experimental and computational research in thermal management, electronics cooling and energy systems. The group combines laboratory measurement with high fidelity simulation and works with industry partners in Ireland and internationally. This post supports an externally funded research programme in the modelling and simulation of thermal systems, delivered with external research and industry collaborators. The successful candidate will lead the technical delivery of a defined package of modelling and software work under the direction of the Principal Investigator. This is a software-focused post. The work involves implementing numerical methods and machine learning models in code, building reduced-order and hybrid surrogate models that meet real-time performance targets with quantified error bounds, defining modelling standards and input and output conventions, automating model generation and packaging, integrating models into a wider software platform, and validating models against experimental and operational data. The post is weighted towards software development, and applicants will be asked to evidence code they have personally written. The role involves coordination with external collaborators, including some travel for project meetings and site visits, and offers strong scope for peer-reviewed publication and industry engagement.

Role Description

The work on this Research Programme is carried out by Postdoctoral Research Fellows and Senior Postdoctoral Research Fellows and is quasi-autonomous research activity. The mentoring Principal Investigator (PI) will advise the appointee on the conduct of their research which itself will be part of a research programme that the PI is responsible for. The intention is that during the employment of the appointee, they will avail of learning opportunities provided by TU Dublin and/or external agencies related to their particular research programme or research practice in general. At the completion of the Senior/Postdoctoral Research Fellowship period, the appointee will be expected to leave the University and continue their academic formation and development in a different research environment. At the completion of the mentored training period, the appointee should be in a position to take up employment as a fully autonomous researcher with another employer.

The ideal candidate will demonstrate the appropriate mix of knowledge, experience, skills, talent and abilities required for the role as outlined below and must satisfy all of the essential criteria:

• 1. A PhD or equivalent in mechanical, thermal, energy or aerospace engineering, applied mathematics, physics, computer science, scientific computing or a closely related discipline.
• 2. Evidence of a research profile and publication record within the requisite subject area.
• 3. Knowledge of research techniques and methodologies.
• 4. Commitment to high quality research.
• 5. Demonstrated ability to develop and maintain research software, evidenced by a code repository, an open-source contribution, or a substantial codebase the applicant has personally authored, together with a clear account of their own contribution to it.
• 6. Demonstrated experience of implementing numerical methods or machine learning models in code, in Python or a comparable language, including use of a scientific computing stack such as NumPy, SciPy and pandas or equivalent.
• 7. Experience of software engineering practice in a research context, including version control such as Git, structured and reusable code organisation, testing and technical documentation.
• 8. Working knowledge of heat transfer, fluid mechanics or thermodynamics sufficient to formulate, calibrate and validate physics-based models of thermal systems, and to interpret experimental or operational measurement data.
• 9. Effective written and verbal communication skills, with the ability to present complex technical information to academic and industry audiences and to produce clear technical documentation. Candidates will be shortlisted based on their demonstration of meeting every essential criterion, so are asked to clearly outline how their experience and qualifications meet the criteria.

Specific Requirements

• 1. Experience of reduced-order modelling or model order reduction, for example proper orthogonal decomposition, dynamic mode decomposition or machine learning surrogates.
• 2. Experience of machine learning frameworks such as PyTorch, TensorFlow or scikit-learn applied to physical or engineering systems.
• 3. Experience of computational fluid dynamics, conjugate heat transfer or finite element thermal analysis.
• 4. Experience of high performance computing or cloud computing environments, including containerised deployment.
• 5. Experience of collaborative research with industry partners or within multi-partner research projects

Candidates may be shortlisted on the basis of none, one or more of these desirable criteria and are asked to clearly outline how their experience and qualifications meet the criteria.