Research Studentships for a Master student

Instituto de Engenharia Mecânica; Portugal; Sur place; EUR 12 000 - 13 000; Plein temps

Résumé du poste

Instituto de Engenharia Mecânica, em Lisboa, oferece uma Research Studentship para Master students com início previsto em novembro de 2026, por 3 meses, com possibilidade de renovação até 12 meses. Bolsa mensal de 1.090,98 € mediante transferência eletrónica.

A investigação centra‑se em CFD com ML para aplicações em energia eólica, exigindo experiência em Python e bibliotecas como PyTorch, OpenCV, Scikit-learn, Pandas, NumPy, Matplotlib, HuggingFace e MLflow.

Qualifications

• Inscrição num mestrado integrado ou mestrado em curso com declaração de honra até a conclusão do contrato.
• Experiência comprovada em Generative Adversarial Learning para avaliação de viés.
• Conhecimento de Python e bibliotecas associadas (PyTorch, OpenCV, Scikit-learn, Pandas, NumPy, Matplotlib, HuggingFace, MLflow).

Responsabilités

• Contribuir para o projeto de CFD com ML aplicado a aplicações de energia eólica.
• Desenvolver modelos de IA para acelerar cálculos CFD e escalabilidade.
• Gerar dados de treino de alta qualidade para aplicações em energia renovável.
• Documentar o trabalho desenvolvido e produzir resultados para conferências/publicações.

Connaissances

Generative Adversarial Learning

Python programming

Formation

Mestrado integrado ou em curso

Outils

Python

PyTorch

OpenCV

Scikit-learn

Pandas

NumPy

Matplotlib

HuggingFace

MLflow

Description du poste

Organisation/Company Instituto de Engenharia Mecânica Research Field Engineering » Mechanical engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Application Deadline 23 Oct 2026 - 18:00 (Europe/Lisbon) Country Portugal Type of Contract Not Applicable Job Status Not Applicable Offer Starting Date 1 Nov 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number BI 32.PE756.2026.IDMEC Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Reference: BI 32.PE756.2026.IDMEC

Research Studentship for Master students

Applications are open for one (1), Research Studentships for a Master student within the framework of Project 1803P.00756.1.01, PE756-DATAZ - PE756-IDMEC, financed by IDMEC funds, under the following conditions:

Scientific Area:Mechanical Engineering, Intelligent Systems.

Admission Requirements:

• To be enrolled at an integrated master or a master, ordeclaration of honor in which undertakes to be enrolled until the grant's contract is done;
• not to exceed with this contract, including the possible renovations, an accumulated period of two years in this type of studentship, continuously or with interruptions;
• proved experience in Generative Adversarial Learning for Bias Assessment
• programming experience in Python, including PyTorch, OpenCV, Scikit-learn, Pandas, Numpy, Matplotlib, HuggingFace and MLflow.

Workplan and the objectives to achieve:

This project focuses therefore on current, wave and offshore wind applications. Current, wave, and offshore wind energy harvesters are complex systems whose design needs to find a delicate balance between fluid dynamics, electro-mechanical performance, and safety. Computational Fluid Dynamics (CFD) methods, widely used for this purpose, require large amounts of computational resources. However, poor scalability of the current CFD methods limits their applications. CFD have started applying Machine Learning (ML) algorithms to enhance the capabilities of traditional tools. This project introduces ML methods in the traditional CFD framework to speed up the turn‑around computational time and scalability of the SIMPLE algorithm. The objectives to achieve within this project are:

• The solution of the pressure Poisson equation will be attempted using matrix solvers utilizing ML for acceleration.
• The nonlinear loops of the pressure‑velocity coupling will be improved by leveraging ML models to substantially improve the classical SIMPLE approximations,
• A complete replacement of the SIMPLE algorithm by ML methods will be attempted.
• Generation of high‑quality data for training, which HYBRID will tackle specifically for renewable energy applications.

The grant holder will develop Artificial Intelligence models (Surrogate Models) in HPC. Design and development of the end‑user interface will also be considered. The grant demands written documentation of all developed work. Further, the research results must result in papers to be submitted to conferences and journals.

Legislation and Regulations:Statute of Scientific Research Fellow, approved by Law nr. 40/2004, of August 18, as worded by Decree‑Law nr. 123/2019, of August 28; IDMEC Regulation for Research Studentships and Fellowships, available on https://www.idmec.tecnico.ulisboa.pt/

Workplace:The work will be developed at IDMEC - Institute of Mechanical Engineering, being both the Host and Contracting Entity, and under the scientific supervision of Prof. João Miguel da Costa Sousa.

Duration:The research fellowship will have the duration of 3 months. It’s expected to begin in November 2026, and may be eventually renewed up to the maximum of 12 months.

Obtaining an academic degree during the term of the contract is not a reason for changing the contractual conditions.

Monthly maintenance allowance:The amount of the monthly maintenance allowance is €1090,98 being the payment method by Wire Transfer.

Selection methods: The selection methods will be the following: a) curriculum evaluation (70%), b) individual interview (specifying its conditions) (30%) with the total weight of 100%. The interview is not compulsory, if the curriculum of the candidates is considered to be sufficient for evaluation.

Composition of the selection Jury: Prof. João Miguel da Costa Sousa (President of the Jury), Prof. Susana Margarida da Silva Vieira (Vowel), Doctor Miguel de Sousa Esteves Martins (Vowel).

Selection minutes: Brief minutes of the jury meetings will be drawn up, indicating the names and affiliation of the jury members, the names of the excluded and admitted candidates, the criteria and respective assessment by candidate, ranking of candidates, and all decisions must have clear and sufficient grounds. The minutes must be accompanied by declarations of conflict of interest (CDI) of all members of the jury.

Announcement/ notification of the results: The final evaluation results will communicated to all applicants by email.

After be notified, candidates have 10 working days to submit a formal rebuttal, by email.

Application deadline and formalization: The call is open in the period between October 12 and October 23, until 18:00, 2026.