PhD Thesis “Self-Driving Lab for Investigating the Effects of Accelerated Stress Testing in Water Electrolysis Cells”

AIT Austrian Institute of Technology GmbH; Wien; On-site; EUR 36,000 - 48,000; Full time

Benefits offered by this job

PhD community access

PhD supervision support

Inclusive work environment

Job summary

AIT Austrian Institute of Technology GmbH in Vienna seeks a PhD candidate to join the Center for Energy. You will help transform materials research into a fully digital, data-driven workflow, piloting automated research processes and collaborating across robotics, software, electrochemistry, and materials science.

You will develop robotic automation for accelerated stress testing and FAIR data pipelines, while applying ML and Bayesian optimization to improve testing strategies.

Qualifications

• Master's level or higher in a technical field with ability to defend within 3 months after start.
• Strong Python programming skills and data analytics experience.
• Hands-on experience with laboratory automation, robotics, and hardware-software interfacing.
• Experience with ML frameworks (PyTorch, TensorFlow) and data-driven workflows.

Responsibilities

• Support the ECHT team in transitioning materials research to a data-driven pipeline.
• Pilots end-to-end automated and autonomous research workflows within the ARA-ESM platform.
• Develop, assemble, and operate a robotic platform to automate AST protocols for water electrolysis cells.
• Collaborate with Data Steward to establish FAIR-compliant, automated data capture and structuring pipelines.
• Apply machine learning, surrogate modeling, and active learning to link testing with degradation and performance metrics.
• Implement closed-loop strategies (e.g., Bayesian optimization) to autonomously plan and refine tests.
• Publish results in peer-reviewed journals and present at international conferences.
• Collaborate with robotics, software engineering, electrochemistry, and materials science experts within ARA.

Skills

Python programming

Machine learning

Laboratory automation

Robotics interfacing

REST APIs

Data management (FAIR)

Independent scientific work

English language

German language

Education

Master's in Mechatronics / Materials Science / CS / EE / Physics / Chemistry

Tools

Python data libraries (Pandas, NumPy, SciPy)

PyTorch / TensorFlow

REST APIs

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 digitalized 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.
• You will play a central role within the ARA-ESM platform (Energy Conversion and Storage Materials) by piloting end-to-end automated and autonomous research workflows.
• You will develop, assemble, and operate a robotic platform to automate accelerated stress testing (AST) protocols for water electrolysis cells in conjunction with subsequent material characterisation.
• You will collaborate closely with the team’s Data Steward to establish FAIR-compliant, automated data capture, ingestion, and structuring pipelines for all experimental test sequences.
• You will apply machine learning, surrogate modeling, and active learning algorithms to link testing conditions with measured degradation phenomena and performance metrics.
• You will implement closed-loop strategies (e.g., Bayesian optimisation) to autonomously plan, execute, and refine subsequent testing parameters based on real-time data evaluation.
• You will publish your results in peer-reviewed journals and present your research findings at international scientific conferences.
• You will collaborate actively with interdisciplinary experts across robotics, software engineering, electrochemistry, and materials science within the ARA ecosystem.

Your Qualifications As An Ingenious Partner

• Master's studies in the field of Mechatronics, Materials Science, Computer Science, Electrical Engineering, Physics, Chemistry, or a related technical field. (Your master’s degree does not need to be completed before your start date, but you should realistically be able to complete it within three months after starting the position.)
• Very good programming skills in Python, including relevant data libraries (e.g., Pandas, NumPy, SciPy) and workflow automation.
• Practical experience or strong interest in laboratory automation, robotics, and hardware-software interfacing (e.g., via REST APIs).
• Hands-on experience or sound theoretical background in machine learning and application of related frameworks (e.g., PyTorch, TensorFlow).
• Solid understanding of water electrolysis or electrochemistry in general as well as familiarity with material characterisation methods would be an advantage.
• Basic understanding of Research Data Management (RDM) and FAIR principles would be an advantage.
• Demonstrated ability for independent scientific work, critical thinking, and motivation to publish in peer-reviewed journals and present at international conferences.
• High level of commitment and curiosity for interdisciplinary problem-solving will be appreciated.
• Very good command of English (spoken and written) is essential, German language skills are an asset.

Additional Conditions

• Duration of the PhD project: 3 years.
• Start date: 01.2027 – however, there is some flexibility concerning the start date.
• You are required to enroll for a PhD programme at an Austrian or foreign university within 6 months including a binding agreement with an academic supervisor.

What To Expect

• EUR 2.832,10 gross per month (14 times / year), for 30 h / week
• In addition to numerous events, seminars, networking opportunities and additional company benefits, you will be part of our AIT PhD Community with around 150 international students. As a research institution, we are familiar with the supervision and execution of PhD theses, and we are looking forward to supporting you accordingly!

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.