In addition to original research in data-driven computational modelling and associated numerical methods, as part of the research team led by Prof. Dr.-Ing.
Andreas Zilian (Computational Engineering / FSTC), the position will be actively involved in the creation of a Computational and Data Engineering Hub for
Luxembourg and will support the Doctoral Training Unit
Data-driven Modelling and Applications (DRIVEN).
Conceptualise the Computational and Data Engineering Hub for Luxembourg
Contribute to teaching and doctoral training
PhD in the domain of Computational Engineering
Interest in Statistical Analysis and/or Machine Learning
Experience with Python/C++ programming, HPC and associated software development environments
Track record in graduate/doctoral education
Excellent trans-disciplinary communication skills
Very good command of English
Willingness to work in a multilingual and international environment
Ability to work independently and as part of a team.
A dynamic and well-equipped research environment
Access to a rich network in science and industry
Continuous training in scientific and professional skills
Personal work space at the University of Luxembourg.
Gender policy: UL strives to increase the proportion of female researchers in its faculties. Therefore, we explicitly encourage women to apply.
Application submission: Before proceeding with the submission of your application, please prepare the following documents.
Curriculum vitae (maximum two pages)
Motivation letter (maximum two pages) detailing how you meet the selection criteria
Research statement (maximum two pages) outlining your scientifc interests and describing your specific research perspectives
Publication list and PDFs of those publications
Doctoral thesis (final or draft, if draft, then state the expected submission date)
Full contact details of two persons willing to act as referees
Copies of diplomas, transcripts with grades, with English, French or German translation
All documents should be uploaded in PDF format via the UL online submission system until15 April 2019. Early submission is encouraged ;
applications will be processed upon arrival. Please note that incomplete applications as well as applications sent by e-mail will not be considered.
Selection process: Candidates will be shortlisted based on the criteria detailed above. Shortlisted candidates will be invited for an interview and/or interviewed by phone.
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