Machine Learning Researcher | IS Team (Job Ref.: AICOS_Jobs_2025_03) | Lisboa, Portugal Lisboa

Machine Learning Researcher | IS Team (Job Ref.: AICOS_Jobs_2025_03) | Lisboa, Portugal
Lisboa
Lisboa, Lisboa, Portugal

Job Title: ML Researcher

Job Ref: AICOS_Jobs_2025_03

Job Type: Full-time contract.

Job Location: Lisbon, Portugal.

Job Description And Responsibilities

Fraunhofer Portugal AICOS is seeking a talented
- level Machine Learning Researcher 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
- edge research and
- world impact. You will contribute to initiatives that enhance industries, promote social
- 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.

Your Role

1. Synthetic Data Generation:
   
   Research and develop methods for generating synthetic data across one or multiple modalities; Explore the use of synthetic data for various applications, including healthcare and
   - purpose domains; Investigate how synthetic data can enhance privacy and improve model robustness in different scenarios; Design and implement evaluation frameworks to assess the quality of synthetic data and its suitability for
   - world use cases.
2. Data & Model Auditing:
   
   Evaluate data quality (including
   - world and synthetic data) and model performance, identifying potential gaps or vulnerabilities; Integrate synthetic data into auditing workflows, determining where it can (and cannot) be an asset; Develop transparent reporting mechanisms, such as data and model cards, to communicate findings effectively and guide
   - making.
3. Collaboration and Maintenance:
   
   Work closely with multidisciplinary teams to integrate synthetic data strategies into existing pipelines and platforms; 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
   - edge ML methods related to synthetic data and model auditing methodologies.

Your Profile

1. Academic Qualifications: Master’s degree or equivalent qualifications in Biomedical Engineering.
2. Technical Skills:
   
   Programming proficiency in Python and experience with machine learning frameworks such as Py
   Torch or Tensor
   Flow; Generative Models: Experience with GANs, VAEs, diffusion models, or other generative architectures; Evaluation of Synthetic Data: Understanding of metrics and methods to measure fidelity, privacy, and robustness of synthetic datasets.
3. Other skills:
   
   Excellent English communication skills (technical and general audiences); Capacity to translate research findings into actionable insights for
   - world applications.

We Value

1. Familiarity with biosignals, time series is a plus;
2. Experience or interest in advancing robust ML solutions that maintain performance under diverse and challenging conditions;
3. Commitment to clear and honest communication of data and model limitations using established reporting standards and tools;
4. A track record (or strong desire) for academic or industrial research, with publications or demonstrable project experience in ML;
5. Ability to work effectively in multidisciplinary and
   - functional teams;
6. Autonomous, dependable, proactive, and a
   - thinking team player.

Why Should You Join Fraunhofer Portugal

1. Innovative Environment: Be part of a
   - centric workplace that fosters creativity and
   -
   -
   - box thinking. We encourage the development of new ideas and ensure that every voice is heard;
2. Research with Impact: Engage in projects that sit at the intersection of research and
   - world applications, contributing to technology that makes a tangible difference in society;
3. Multidisciplinary Teams: Collaborate with professionals from diverse backgrounds, enhancing your learning and professional growth;
4. Professional Excellence: Work within a culture that upholds professional standards and best practices, promoting continuous improvement and excellence in research;
5. Flexible Work Arrangements: Benefit from flexible working hours and opportunities to work from home, supporting a healthy
   - life balance;
6. Comprehensive Benefits: Benefit from a partially funded health insurance plan, and a variety of additional perks;
7. 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 10th of February 2025. The selected candidate is expected to start working in March 2025. Applications must be made to the email jobs@fraunhofer. pt and contain:

1. CV – mandatory;
2. Motivation Letter;
3. Recommendation Letters are optional but also welcome.

Observation

The research activities in the scope of this job opportunity are planned to be developed within the framework of projects:

1. ACHILLES – Human-centred Machine Learning: Lighter, Clearer, Safer, with Notice No. HORIZON-CL4-2024-DATA-01-01 and Project Reference No. 101189689;
2. AISym4Med – Synthetic and Scalable Data Platform for Medical Empowered AI, with Notice No. HORIZON-HLTH-2022-IND-13-02 and Project Reference No. 101095387;
3. MARTA – Machine-learning Auditing for Robust and Transparent Administration, with Notice No. 04/C05-i08/2024;
4. Next
   Gen
   AI – Center for Responsible AI, with Notice No. 01/C05-i01/2021 and Project Reference No. 62 - C645008882-00000055.