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# Job offer

- **Company:** Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
- **Location:** Castelldefels, Spain (Remote available)
- **Contract:** Temporary contract
- **Skills:** Training Data, Artificial Intelligence, Artificial Neural Networks, Computer Programming, Python (Programming Language), Machine Learning, Cyber-physical Systems, Scientific Computating, Signal Processing, Deep Learning, Information Technology, Data Analytics
- **Published:** September 22, 2026
- **Apply:** https://www.cttc.cat/job/call-25-2026-1-post-doc-research-position-in-the-sustainable-artificial-intelligence-research-unit/

## About the Role

PhD or equivalent, * We are looking for a highly motivated, enthusiastic, energetic person, aiming at significantly improving his or her career perspectives in both public and private sectors. The successful applicant should have the competencies of the R2 category.

 * Required qualification/skills/experience:
 + PhD in Computer Science, Data Science, Applied Mathematics, Signal Processing, or related field (at the time of signing the contract)
 + Background in machine learning and scientific computing. [10 points]
 + Strong programming experience in Python and/or Julia [8 points]
 * Valuable qualifications/skills/experience
 + Experience with physics-informed neural networks or ordinary neural differential equations (ODEs) [10 points]
 + Experience with operator learning (e.g., Koopman operator, kernel methods) [8 points]
 + Experience with differential equations, particularly stiff ODEs [8 points]
 + Strong publication record and communication skills [8 points]
 + Familiarity with Scientific Machine Learning (SciML) frameworks [5 points]
 + Demonstrated contributions to open-source libraries on the topic [3 points]

Even if you do not meet all the technical requirements, we encourage you to apply

The candidates past performance but also future potential will be considered as criteria for selecting researchers.

Languages
ENGLISH

## Description

The Sustainable Artificial Intelligence (SAI) research unit is seeking a highly motivated postdoctoral researcher to join an internal research project focused on developing novel data-driven approaches for anomaly and novelty detection problems in cyber-physical systems. Moving beyond the classical mechanistic modeling paradigm, this exciting opportunity combines cutting-edge scientific computing methods and emerging computational tools, such as physics-guided learning and operator-theoretic system identification, to enhance the robustness of anomaly/novelty detection. The objective is to develop next-generation high-fidelity detection methodologies that overcome the classical barriers of traditional machine and deep learning models, such as (i) the significant amount of complete and well-balanced training data to identify and interpret abnormal events (e.g., cyber-attacks), (ii) the non-stationary and/or unforeseen data distributions, and (iii) irregular (and often rare) anomalous
patterns during system transients.

The position holder will be joining the research activities of the SAI research unit and will be required to carry out fundamental research and disseminate results through scientific publications in high-quality journals and top-tier international conferences, as well as to organize special sessions and workshops on the research topics of the project.


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