Data Steward (f/m/d) - AIT Research Acceleration Platform for Energy Conversion and Storage

AIT Austrian Institute of Technology; Wien; Sur place; EUR 55 000 - 75 000; Plein temps

Résumé du poste

AIT Austrian Institute of Technology in Vienna is seeking a Data Steward for the Energy Conversion and Storage Materials platform (ARA-ESM). You will implement data structures, metadata schemas, and governance to enable FAIR data and automated analytics across research workflows.

The role focuses on data pipelines, ELNs/LIMS integration, dashboards, and collaboration with domain experts to accelerate material discovery and sustainable energy solutions.

Qualifications

• Master’s or PhD in a technical field.
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Responsabilités

• You will support the ECHT team in building a digitalised, data-driven pipeline for rapid energy technology innovation.
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Connaissances

Research Data Management

FAIR data principles

Metadata standards

Data governance

Collaborative work

Formation

Master’s or PhD in Data Science, Computer Science, Materials Science, Chemistry, or Physics

Outils

Python

Pandas

NumPy

APIs

Description du poste

The AIT Austrian Institute of Technology is Austria’s largest Research and Technology Organisation (RTO). We aim to transform scientific excellence into innovation with impact. Together with our partners, we develop technologies and solutions for a sustainable, resilient, and digitalised future, strengthening Europe’s competitiveness and technological sovereignty. Our international teams combine cutting-edge research with strong implementation expertise to create measurable value for industry and society.

Our Center for Energy is looking for new Ingenious Partner for our location in Vienna (Giefinggasse, 1210). In the Center for Energy, we develop sustainable, resilient energy systems to drive the green transition. As part of our digital transformation strategy, the AIT Research Acceleration Platform (ARA) integrates cutting-edge process automation, digital infrastructure, and data governance to accelerate scientific breakthroughs across disciplines such as novel battery materials, energy conversion and storage materials, microbiome engineering in agriculture or light-metal alloys.

Our team Energy Conversion and Hydrogen Technologies (ECHT) is a critical part of this platform, specifically with Energy Conversion and Storage Materials platform (ARA-ESM) dedicated to developing novel materials for clean energy technologies like water electrolysis and CO2 conversion. A major focus lies on combining high-throughput synthesis, advanced fast-track characterisation, and digitalised research workflows to accelerate the discovery of sustainable, durable, and high-performance solutions.

Data Steward (f/m/d) - AIT Research Acceleration Platform for Energy Conversion and Storage Materials

Your respnsibilities:

• You will support the ECHT team in its mission of transforming traditional materials research into a fully digitalised, data-driven pipeline forrapid energy technology innovation.
• Your tasks involve implementing standardised data structures, metadata schemas, and domain ontologies for material deposition, characterisation, and electrochemical testing to ensure full compliance with FAIR data principles and enable downstream automated analytics.
• You will design, build, and maintain robust data pipelines to automate the ingestion, processing, and curation of complex experimental datasets directly from synthesis systems and analytical instruments.
• You will establish and enforce clear data governance frameworks, Data Management Plans (DMPs), and access policies across the ARA-ESM domain to guarantee data integrity and security.
• You will develop intuitive APIs, connectors, and integration workflows to link electronic lab notebooks (ELNs), laboratory information management systems (LIMS), and central data repositories.
• You will create interactive dashboards and data visualisation tools that empower domain researchers to easily explore, query, and interpret multi-dimensional material properties.
• You will collaborate with domain experts to prepare high-quality, interoperable datasets and support the deployment of machine learning models for predictive material discovery.

Your qualifications as an Ingenious Partner:

• Completed studies (Master’s or PhD) in Data Science, Computer Science, Materials Science, Chemistry, Physics, or a related technical field.
• Proven experience in Research Data Management (RDM), metadata standards, and practical implementation of FAIR principles and knowledge of European data management regulations (EU Data Act, EU AI Act). .
• Strong programming skills in Python, including relevant data libraries (e.g., Pandas, NumPy,