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

AIT Austrian Institute of Technology GmbH; Wien; On-site; EUR 51,000 - 62,000; Full time

Benefits offered by this job

Canteen and meal allowance

Flexitime and up to 50% home office

Travel support for conferences

Pension fund

Job summary

AIT Austrian Institute of Technology in Vienna seeks an Ingenious Partner to advance digitalised energy materials research. You will implement data structures, ontologies, and data pipelines across ELNs, LIMS and central repositories, ensuring FAIR compliance and enabling automated analytics.

The role emphasizes collaboration with energy researchers, dashboards, and ML support, with a strong emphasis on governance and secure data handling. Fluent English is essential; German is a plus.

Qualifications

• Master’s or PhD in a technical field including Data Science, CS, Materials Science, Chemistry or Physics.
• Experience in Research Data Management (RDM) and FAIR data principles.
• Strong Python programming and data libraries knowledge (Pandas, NumPy, SciPy).
• Software engineering principles with Git and CI/CD experience.
• Familiarity with semantic web technologies and ontologies (RDF/OWL/JSON-LD/EMMO).
• Experience with ML frameworks (PyTorch, TensorFlow, Scikit-Learn) is an advantage.
• Proficient in English; German is an asset.

Responsibilities

• Support the ECHT team to digitise materials research workflows.
• Implement standardised data structures, metadata schemas, and ontologies.
• Design, build, and maintain data pipelines for datasets from synthesis and analyses.
• Establish data governance, DMPs, and access policies for data integrity and security.
• Develop APIs and integration workflows linking ELNs, LIMS, and central data repos.
• Create dashboards and visualization tools for researchers to explore material properties.
• Collaborate with domain experts to prepare interoperable datasets and ML model deployment.

Skills

Python

RDM

Metadata standards

FAIR data principles

Team collaboration

English proficiency

Education

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

Tools

Pandas

NumPy

SciPy

Git

CI/CD

Jupyter

RDF

OWL

JSON-LD

EMMO

PyTorch

TensorFlow

Scikit-Learn

Plotly

Dash

Job description

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 CO 2 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.

CENTER FOR ENERGY

• You will support the ECHT team in its mission of transforming traditional materials research into a fully digitalised, data-driven pipeline for rapid 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, SciPy) and workflow automation.
• Solid background in software engineering principles, including scalable architecture, automated testing, version control workflows (Git), and CI/CD pipelines.
• Hands‑on experience with semantic web technologies, knowledge representation, and ontologies (e.g., RDF, OWL, JSON-LD, EMMO) is an advantage.
• Principal understanding of laboratory data from material synthesis, characterisation, or electrochemical testing is an advantage.
• Familiarity with interactive visualisation tools (e.g., Plotly, Dash) and foundational machine learning frameworks (e.g., PyTorch, TensorFlow, Scikit‑Learn).
• High level of commitment, strong team spirit, and an enthusiasm for continuous learning and professional development.
• Very good command of English (spoken and written) is essential, German language skills are an asset.

What To Expect

• Start-Date: 01.01.2027
• The minimum gross annual salary on a full-time basis (38,5 h / week) according to the collective agreement is EUR 56.784,--. The actual salary will be determined individually, based on your qualifications and experience. In addition, we offer company benefits, flexible working conditions, individual training and career opportunities.
• Highlights of our employee benefits include a canteen and meal allowance, organic coffee, tea and fruit baskets, preventive healthcare benefits and company doctor, pension fund, additional days off for various life events, family benefits (including two weeks of paid paternity leave "Papa-Weeks" and leisure subsidies), voucher programme, sports, cultural and socialising events and many more, as well as flexitime models (incl. up to 50% home office), travel support for conferences and networking, and individual training and career development opportunities.

At AIT, we create an inclusive and family-friendly working environment that promotes equal opportunities and actively strengthens diversity across our workforce and in leadership positions. Among other initiatives, we are committed to increasing the proportion of women in our company and therefore particularly welcome applications from female applicants.