AIT Austrian Institute of Technology
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PhD Thesis in Self-Driving Lab for Accelerated Stress Testing in Water Electrolysis Cells AIT Austrian Institute of Technology in Austria
Degree Level
PhD
Field of study
Computer Science
Funding
PhD position for 3 years at 30 h/week with a gross salary of EUR 2,832.10 per month paid 14 times per year. The post is part of AIT's PhD Community and includes events, seminars, networking opportunities, and company benefits.
Country
Austria
University
AIT Austrian Institute of Technology

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About this position
AIT Austrian Institute of Technology is advertising a PhD thesis in Self-Driving Lab for Investigating the Effects of Accelerated Stress Testing in Water Electrolysis Cells at its Center for Energy in Vienna, Austria.
The project sits within the Energy Conversion and Hydrogen Technologies team and the AIT Research Acceleration Platform (ARA), with a strong focus on energy conversion and storage materials, water electrolysis, accelerated stress testing, robotics, laboratory automation, machine learning, active learning, and Bayesian optimisation. The successful candidate will help build and operate a robotic platform, automate experimental workflows, and connect testing conditions with degradation and performance data.
The role includes FAIR-compliant data capture and structuring, collaboration with a Data Steward, and the use of surrogate modelling and closed-loop optimisation to refine experiments in real time. The PhD student will also publish in peer-reviewed journals and present at international conferences while working with interdisciplinary experts in robotics, software engineering, electrochemistry, and materials science.
Eligibility highlights: applicants should be enrolled in or close to completing a master's degree in Mechatronics, Materials Science, Computer Science, Electrical Engineering, Physics, Chemistry, or a related technical field. Strong Python skills are required, and experience or interest in lab automation, robotics, machine learning, electrochemistry, and research data management is highly relevant. Very good English is essential; German is an asset.
Funding: 30 h/week, EUR 2,832.10 gross per month, paid 14 times per year, for a 3-year PhD project. The position is part of AIT's PhD Community with events, seminars, networking opportunities, and additional company benefits.
Application: apply online with CV, cover letter, certificates/transcript of records, and proof of identity. The start date is flexible, indicated as 01/2027, and the candidate must enroll in a PhD programme at an Austrian or foreign university within 6 months together with a binding academic supervisor agreement.
Funding details
PhD position for 3 years at 30 h/week with a gross salary of EUR 2,832.10 per month paid 14 times per year. The post is part of AIT's PhD Community and includes events, seminars, networking opportunities, and company benefits.
What's required
Master's studies in Mechatronics, Materials Science, Computer Science, Electrical Engineering, Physics, Chemistry, or a related technical field; the master's degree does not need to be completed before the start date but should be completable within three months after starting. Very good Python programming skills with data libraries such as Pandas, NumPy, and SciPy are required. Practical experience or strong interest in laboratory automation, robotics, and hardware-software interfacing is expected. Hands-on experience or a solid theoretical background in machine learning and frameworks such as PyTorch or TensorFlow is desired. Knowledge of water electrolysis, electrochemistry, material characterisation, research data management, and FAIR principles would be an advantage. Very good English is essential; German is an asset. The candidate must enroll in a PhD programme at an Austrian or foreign university within 6 months and have a binding agreement with an academic supervisor.
How to apply
Submit the complete application online with CV, cover letter, relevant certificates/transcript of records, and proof of identity. Apply via the online application portal on the job listing page.
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