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PhD position: Development of a Calphad database ... (No replies)
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A 3-year PhD position available from January 1, 2022 is open in the Computational Materials Science (CMS) group at the Department of Materials Science, Montanuniversität Leoben, Austria.
Short project description
The critical development trends in the 21st century include sustainability, energy saving and recycling. In particular, when applied to structural materials such as steels, the latter inevitably leads to an increased amount of tramp elements. Their influence is often unknown or not fully characterised. This gap must be filled to allow for a knowledge-based design of novel steels.
In this project, we will aim at including ab initio data into the Calphad databases. We will
combine our own ab initio/machine-learned atomistic data with data available in large online data repositories (e.g. Materials Project, NoMaD or AFLOW). We will thus extend existing thermodynamic databases to more exotic tramp and trace species (e.g., Sn, Sb or As).
The position is a part of the Christian Doppler Laboratory for Knowledge-Based Design of Advanced Steels (KnowDAS)–From Ab Initio Methods to Components Produced with low CO2 Emissions. In parallel with this position, another three positions focused on experimental work will be funded in CDL-KnowDAS.
The gross salary for 40 hours/week contract is € 3 058.60 (14× per year).
Your profile
The interested candidate should have a Master’s degree (or equivalent) in Materials Science, Physics, Chemistry or a related subject, be strongly self-motivated, be fluent in English (German is optional) both in oral and written, be a good team player and possess the ability for independent work and scientific publication. A prior experience with thermodynamic modelling (the Calphad method) is essential; hands-on knowledge of any DFT code (preferably VASP) or molecular dynamics (MD) is strongly beneficial. Excellent programming skills, mainly using Python, are a must; experience with Linux/Unix systems and compiling codes at high-performance computer clusters will be considered an advantage.
How to apply
The application should contain:
• a motivation letter,
• a CV,
• a study transcript (in English), and
• two contacts that could provide a recommendation.
All these documents, bundled as a single PDF file, shall be sent to Dr. David Holec ([email protected]) before November 1, 2022. Evaluation of the application and interviews with potential candidates will start immediately and continue until the position is filled. Montanuniversität is an equal opportunity employer.
About the CMS group
The Computational Materials Science group (http://cms.unileoben.ac.at/) applies quantum-mechanical and atomistic modelling techniques to tackle current materials science problems and challenges. The interests span from structural (structure prediction, phase stability, defects, etc.) to functional properties (e.g., surface adsorption, electronic and optical properties) and cover various material classes, from bulk intermetallic alloys to nitride and oxide thin films to carbon and gold nanostructures. A particular strength of the group lies in close collaboration with experimentalists at the Montanuniversität Leoben and numerous national and international institutions.