Machine Learning Researcher | IS Team (Job Ref.: AICOS_Jobs_2025_05) | Lisboa, Portugal Lisboa

Machine Learning Researcher | IS Team (Job Ref.: AICOS_Jobs_2025_05) | 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. Anomaly Detection & Uncertainty Quantification:
   
   Develop and integrate methods for identifying anomalies or rare cases in datasets, both
   - and
   - model training;
   
   Research and implement techniques for uncertainty quantification (e. g. , Bayesian approaches, ensemble methods, or
   - based models), ensuring robust detection and monitoring capabilities;
   
   Design validation steps to recognize data shifts and
   -
   - distribution examples, improving overall model reliability.
2. Performance Region Characterization:
   
   Explore and apply techniques to characterize model performance across different subgroups or
   - based clusters;
   
   Identify subpopulations with shared attributes and performance patterns, moving beyond direct model interpretation to overall performance insights;
   
   Develop workflows to visualize and explain performance regions, promoting actionable understanding for stakeholders.
3. Collaboration and Maintenance:
   
   Work with interdisciplinary teams to integrate anomaly detection and characterization modules into existing pipelines or 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 reliability and characterization.

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:
   
   Programming proficiency in Python and experience with machine learning frameworks (e. g. ,
   - learn);
   
   Familiarity with anomaly detection, outlier analysis, uncertainty quantification, and unsupervised learning (pattern learning, topic mining, representation learning);
   
   Comfortable designing experiments to evaluate model performance under varied conditions.
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. Experience (or interest) in building pipelines to monitor model performance, including
   - time anomaly detection and error analysis;
2. A track record (or strong desire) for academic or industrial research, with publications or demonstrable project experience in ML;
3. Ability to work effectively in multidisciplinary and
   - functional teams;
4. 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 10 th 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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