Postdoc

We will accept incoming Ph.D. holders who have obtained their Ph.D. abroad, of non-Czech nationality, who are not residents of the Czech Republic or have not spent more than 12 months in the Czech Republic in the last 36 months,

or

Ph.D. holders of Czech nationality who have long-term experience abroad. Long-term foreign experience can be considered to be at least 12 continuous months out of the last 36 months, either in the form of doctoral studies abroad or in the form of employment at a foreign scientific institution, or in combination.

Candidate must be no more than 5 years post PhD (career breaks, e.g. maternity/parental leave; long-term illness, are not counted).

This is a two-round selection process in which successful candidates from the faculty/institute selection process advance to the next round at the university-wide level.

Required expertise: 

Expertise in physics-informed neural networks and neural operators for solving PDEs in engineering problems, combining numerical methods with deep learning and validating the resulting models.

IT4Innovations National Supercomputing Centre, part of VSB – Technical University of Ostrava, is a leading research, development, and innovation centre in the fields of high-performance computing, high-performance data analytics, quantum computing, artificial intelligence, and their applications in other scientific, industrial, and societal fields. It currently operates three supercomputers – Karolina, Barbora and Barbora NG – as well as the first Czech quantum computer, VLQ.  IT4Innovations is actively involved in the European AI Factories network – it is a member of the LUMI AI Factory and coordinates the Czech AI Factory.  IT4Innovations employs more than 250 people in research, IT and administrative roles. For more information, visit www.it4i.cz.

• conducting research and publishing under the guidance of an assigned mentor,
• participating in the preparation and implementation of national or international projects,
• continuously improving his/her qualification,
• contributing to the cooperation with partner institutions.

•  doctoral degree in applied mathematics, computational mechanics, computer science or related disciplines,
• a maximum of 5 years after defending the PhD (not including career breaks, e.g. maternity/parental leave; long-term illness),
• excellent publication track record,
• active participation in national or international projects,
• knowledge of numerical methods for solving PDEs (e.g. finite element or finite volume methods) and of their use in engineering problems,
• hands-on experience with physics-informed neural networks (PINNs) or neural operators (e.g. DeepONet, Fourier neural operators), documented by at least 5 publications in impacted journals or major conferences,
• proficiency in Python and modern deep learning frameworks (PyTorch, JAX or TensorFlow), including training models on GPUs,
• sound understanding of how to combine physical models with data-driven approaches, including error analysis, generalisation and validation against reference solutions,
• active knowledge of the English language.

•  work in a promising organisation,
• salary evaluation according to project conditions and the candidate's experience,
• modern laboratory,
• opportunity to participate in an excellent research team,
• possibility of further education,
• 6 weeks of holidays,
• flexible working hours,
• university kindergarten,
• company catering in the canteen,
• MultiSport card,  
• other employee benefits according to the employer's offer.

• CV,
• motivation letter,
• research proposal,
• number of publications in impacted journals according to WoS and Scopus,
• number of publications on which he/she appears as corresponding author or as 2nd or 3rd co-author,
• at least 1 letter of recommendation from a foreign institution,
• copies of proof of education.