Associação Fraunhofer Portugal ResearchJob Title: Junior Privacy-Preserving ML Scientist
Job Ref: AICOS_Jobs_2025_18
Job Type: Full-time contract.
Job Location: Porto, Portugal.
Job Description and Responsibilities:
Fraunhofer Portugal AICOSis seeking a talented Junior Privacy-Preserving ML Scientist to join our dynamic and multidisciplinary team within the Intelligent Systems group. In this role, you will be at the forefront of technological innovation, working on applied research projects that bridge the gap between cutting-edge research and real-world impact. You will contribute to initiatives that enhance industries, promote social well-being, and improve quality of life. Specifically, you will contribute to the research and development of methodologies to improve the privacy and robustness of ML models. You will also contribute for testing a flexible distributed software framework, which includes federated learning and data governance to support the deployment of privacy-preserving ML pipelines.
Your role:
- Research and develop on collaborative, privacy-preserving and responsible ML in development of computer vison models for image classification, and validation of model evolution;
- Reuse existing federated learning infrastructure, a privacy preserving machine learning approach that enables data scientists and ML engineers to train models without moving the data;
- Train an existing model with more private data, including data diversity assessment and model robustness evaluation to detect weaknesses:
> Apply transparent reporting mechanisms, such as data and model cards, to communicate findings effectively and guide decision-making;
> Evaluate the utility of data augmentation with generative AI (using existing models at Fraunhofer).
- Work closely with multidisciplinary teams to integrate into existing processes:
> Maintain and refine current codebases, adhering to best practices in software development and reproducible research;
> Contribute to strategic discussions on advancing research directions, staying updated on cutting-edge ML methods related to privacy-preserving and responsible ML methodologies.
Your profile:
Academic Qualifications:
- Master’s degree or equivalent qualifications in Biomedical Engineering, Computer Science and Engineering, Electrical and Computer Engineering, Artificial Intelligence, or related studies.
Technical Skills:
- Programming proficiency in Python and experience with machine learning frameworks such as PyTorch or TensorFlow;
- Experience using Git distributed version control system;
- Hands-on experience with frameworks like NVIDIA Flare or Flower is a plus, not essential;
- Familiarity with computer vision or image processing techniques is a plus, not essential.
Other skills:
- Excellent English communication skills (technical and general audiences);
- Capacity to translate research findings into actionable insights for real-world applications.
We value:
- Experience in software engineering or applied research, balancing robust engineering principles with a curiosity-driven approach;
- Understanding of, or strong interest in, security and privacy considerations within distributed ML systems;
- Commitment to clear and honest communication of data and model limitations using established reporting standards and tools;
- Ability to work effectively in multidisciplinary and cross-functional teams;
- Autonomous, dependable, proactive, and a critical-thinking team player.
Why should you join Fraunhofer Portugal:
- Innovative Environment: Be part of a people-centric workplace that fosters creativity and out-of-the-box thinking. We encourage the development of new ideas and ensure that every voice is heard;
- Research with Impact: Engage in projects that sit at the intersection of research and real-world applications, contributing to technology that makes a tangible difference in society;
- Multidisciplinary Teams: Collaborate with professionals from diverse backgrounds, enhancing your learning and professional growth;
- Professional Excellence: Work within a culture that upholds professional standards and best practices, promoting continuous improvement and excellence in research;
- Flexible Work Arrangements: Benefit from flexible working hours and opportunities to work from home, supporting a healthy work-life balance;
- Comprehensive Benefits: Benefit from a partially funded health insurance plan, and a variety of additional perks;
- Supportive Culture: Join a team with an excellent spirit, where collaboration, mutual support, and team achievements are celebrated.
Application Process:
Applications are permanently open until the ideal candidate is selected. The first evaluation of applications will occur on 28th of July 2025.
The selected candidate is expected to start working in September 2025.
To apply:
Send your application to jobs@fraunhofer.pt including:
- Curriculum Vitae (mandatory);
- Motivation Letter;
- Recommendation Letters (optional but welcome).
Note:
The research activities in the scope of this job opportunity are planned to be developed within the framework of the following projects:
- HfPT – Health from Portugal, with Notice No. 02/C05-i01/2022 and Project Reference No. Projeto nº 41 NextGenerationEU (PRR).