IMDEA Materials Institute is a public research organization founded in 2007 by Madrid’s regional government to carry out research of excellence in Material Science and Engineering by attracting talent from all over the world to work in an international and multidisciplinary environment. IMDEA Materials has grown rapidly since its foundation and currently includes more than 120 researchers from 22 nationalities and has become one of the leading research centers in materials in Europe which has received the María de Maeztu seal of excellence from the Spanish government. The research activities have been focused on the areas of materials for transport, energy, and health care and the Institute has state-of-the-art facilities for processing, characterization and simulation of advanced materials.

More information can be found at our webpage.

IMDEA Materials is seeking a Research Assistant to support the development and deployment of FAIR data infrastructure within the FAIR-LAB project, aimed at enabling data-driven research in additive manufacturing (AM) and X-ray computed tomography (XCT).

The selected candidate will work closely with data engineers and researchers to digitalize experimental workflows, structure datasets, and ensure their integration into a FAIR-compliant data ecosystem. This includes supporting the creation of a centralized repository, implementing metadata standards, and preparing datasets for downstream analytics and AI applications.

Unlike a pure data engineering role, this position focuses on data preparation, structuring, and FAIR compliance, acting as a critical bridge between experimental research and scalable data infrastructure.

Main Tasks

• Support the digitalization of experimental workflows in metal additive manufacturing and XCT, including data collection, structuring, and standardization.
• Assist in the implementation and population of a FAIR-compliant data repository, ensuring datasets are properly stored, versioned, and accessible.
• Apply FAIR data principles (Findable, Accessible, Interoperable, Reusable) to experimental datasets, including metadata annotation and validation.
• Support the definition and implementation of metadata schemas, ensuring traceability of materials, process parameters, and experimental conditions.
• Assist in data ingestion and preprocessing pipelines, including cleaning, formatting, and organizing heterogeneous data sources (machine logs, images, simulation outputs, etc.).
• Collaborate with researchers to translate experimental data into structured digital formats, enabling integration into the FAIR-LAB data platform.
• Contribute to the development of basic data analysis and AI workflows, including dataset preparation for machine learning models.
• Support validation and quality control of datasets to ensure consistency, completeness, and usability.

This position is suitable for candidates with a background in Computer Science, Artificial Intelligence, Data Science, or related fields (Bachelor/Master level).

The ideal candidate should have:

• Basic programming skills in Python and familiarity with data handling libraries (e.g., pandas, NumPy).
• Understanding of data structures, databases (SQL/NoSQL), and file formats (CSV, JSON, HDF5).
• Familiarity with machine learning concepts and data preprocessing techniques.
• Interest or basic knowledge in FAIR data principles or scientific data management.
• Ability to work with heterogeneous datasets (images, sensor data, logs).
• Strong attention to detail in data organization, documentation, and validation.
• Ability to work in a multidisciplinary research environment with engineers and scientists.
• Good communication skills and proficiency in English.

Mandatory Requirements

It is important that the candidate meets the requirements indicated in the call:

1. Age (16–29 years old)
2. Degree/qualification (according to the requested profile)
3. Registered as an unemployed job seeker at the emplyment office within the National Employment System (SEPE) before hiring: https://sede.comunidad.madrid/...
4. No employment relationship with IMEDEA (during the 6 months prior to hiring).
   
   The position is supported by Young Researchers Programme of the Community of Madrid within the framework of the ESF+ Programme: Strategic Technologies for Europe Platform (STEP) / Programa de Jóvenes Investigadores de la Comunidad de Madrid en el marco del Programa FSE+: Plataforma de Tecnologías Estratégicas para Europa (STEP)

Other requirements

• Atleast a Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or related field, or about to complete. Masters Degree.
• Basic programming skills in Python
• Knowledge of data structures and databases (SQL or NoSQL)
• Ability to work with structured and unstructured data formats (CSV, JSON, etc.)
• Good level of English (written and spoken)

Valuable Skills but must not have

• Familiarity with scientific data management or FAIR principles
• Experience with data processing libraries (pandas, NumPy)
• Basic understanding of machine learning workflows
• Experience working in Linux environments
• Attention to detail in data organization and documentation

Deadline

Open until a suitable candidate is found

Impact

The selected candidate will directly contribute to building the data foundation of FAIR-LAB, enabling reproducibility, interoperability, and AI-driven insights in additive manufacturing and XCT workflows.

• Full-time contract including social security coverage for 12 months
• The post will remain active and open until filled.