Machine Learning Researcher | IS Team (Job Ref.: AICOS_Jobs_2025_04) | Lisboa, Portugal Lisboa

Machine Learning Researcher | IS Team (Job Ref.: AICOS_Jobs_2025_04) | Lisboa, Portugal
Lisboa
Lisboa, Lisboa, Portugal

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 interpretability and reliability of ML models.

Your role:

1. Interpretability & Concept Learning:
   1. Research and implement methodologies to improve the interpretability of ML models;
   2. Employ
      - supervision (e. g. ,
      - language) to learn
      - interpretable concepts (e. g. , color, scale, texture);
   3. Contribute to the development of a data generator that produces multimodal datasets (images and descriptions) with
      - truth concepts;
   4. Develop pipelines for concept extraction and retrieval, applying them to various domains (e. g. , healthcare, industry);
   5. Investigate how these concepts influence downstream tasks, both discriminative and generative.
2. Reliability & Stress-testing:
   1. Explore and utilize generative models to synthesize data that exposes model pitfalls, like challenging or
      - case samples to evaluate and characterize model performance, identifying vulnerabilities;
   2. Devise systematic approaches for experiment design and analysis to ensure robust and reliable ML systems.
3. Collaboration and Maintenance:
   1. Collaborate with multidisciplinary teams to integrate novel interpretability and reliability techniques into ongoing projects;
   2. Maintain and refine existing codebases, ensuring best practices in software development and research reproducibility;
   3. Contribute to discussions on future research directions, keeping updated on
      -
      -
      - art techniques.

Your profile:

1. Academic Qualifications: Master’s degree or equivalent qualifications in Computer Science, Biomedical Engineering, Electrical and Computer Engineering, or related studies.
2. Technical Skills:
   1. Programming proficiency in Python;
   2. Deep Learning: Solid understanding of neural network architectures and frameworks (e. g. , Py
      Torch, Tensor
      Flow);
   3. Multimodal / Self-Supervised Learning: Familiarity with
      - language models and alignment techniques;
   4. Generative Models: Basic knowledge of GANs, diffusion models, or other generative approaches;
   5. Large Language Models: Experience or willingness to learn how to utilize LLMs (e. g. , GPT-type models), including prompt design;
   6. Experiment Design: Ability to plan and execute experiments methodically, analyzing results for model improvements.
3. Other skills:
   1. Excellent English communication skills (technical and general audiences);
   2. Capacity to translate research findings into actionable insights for
      - world applications.

We value:

1. A track record (or strong desire) for academic or industrial research, with publications or demonstrable project experience in ML;
2. Ability to work effectively in multidisciplinary and
   - functional teams;
3. 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.

- 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:

- ACHILLES – Human-centred Machine Learning: Lighter, Clearer, Safer, with Notice No. HORIZON-CL4-2024-DATA-01-01 and Project Reference No. 101189689;

- MARTA – Machine-learning Auditing for Robust and Transparent Administration, with Notice No. 04/C05-i08/2024;

- Next
Gen
AI – Center for Responsible AI, with Notice No. 01/C05-i01/2021 and Project Reference No. 62 - C645008882-00000055.

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