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Tenure-Track Professorship in AI-Driven Chemical Reactivity and Molecular Design

Klf
CompanyKlf
CategoryEducation
LocationAT
Remote
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
First seen3 Aug 2026 (the employer did not state a posting date)
Last verified11 Aug 2026
SourceThe employer's own careers page (company_site)
Applications are handled by the employer, not by us.Apply on the employer's site →
Description
Tenure-Track Professorship in AI-Driven Chemical Reactivity and Molecular Design Job Details | Universität Wien Please note that you can see the videos on this website only if you accept all cookies! Additionally, you can freely decide and change any time whether you accept cookies or choose to opt out of cookies to improve website's performance, as well as cookies used to display content tailored to your interests. Your experience of the site and the services we are able to offer may be impacted if you do not accept all cookies. Jobs in Research & Teaching Jobs in Administration & Organisation The University of Vienna is internationally renowned for its excellence in teaching and research, and counts more than 7,500 academics from all disciplines. This breadth of expertise offers unique opportunities to address the complex challenges of modern society, to develop comprehensive new approaches, and educate the problem-solvers of tomorrow from a multidisciplinary perspective. The Faculty of Chemistry at the University of Vienna invites applications for a Tenure-Track Professorship in AI-Driven Chemical Reactivity and Molecular Design The position We seek an outstanding candidate in theoretical and computational chemistry whose research lies at the interface of reactive molecular simulations and data-driven modeling. The successful candidate will develop and apply data-driven methods for chemical discovery and molecular design. These methods include machine-learned interatomic potentials, data-efficient and uncertainty-aware modeling, enhanced sampling, and statistical thermodynamics. Research will address property prediction and optimization as well as applications to chemical reactions, photochemistry, and materials design. The successful candidate will work in a dynamic research environment with access to state-of-the-art computational infrastructure, including high-performance computing clusters for molecular simulations and data-driven modeling. Additional support includes access to software licenses and collaborative opportunities across theoretical, synthetic and physical chemistry, including close collaboration with our Cluster of Excellence “Materials for Energy Conversion and Storage”. The research environment is designed to provide optimal conditions for innovative, independent research and integration into international scientific networks. Your academic profile: • Doctoral degree/PhD • Two years of international research experience during or after doctoral studies • Outstanding research achievements, excellent publication and funding record, international reputation • Gender and diversity competence • Experience in designing of and participating in research projects, ability to lead research groups and acquire third-party funding • Enthusiasm for excellent teaching and supervision at the bachelor's, master's, and doctoral level We expect the successful candidate to acquire, within three years, proficiency in German sufficient for teaching in bachelor's programmes and for participation in university committees. We offer: • the opportunity to obtain a permanent position and eventual promotion to full professor; the initial contract as Assistant Professor is limited to six years, after positive evaluation of a qualification agreement the contract becomes permanent as Associate Professor; Associate Professors can be promoted to Full Professor through an internal competitive procedure. • a dynamic research environment • a wide range of research and teaching support services • attractive working conditions in a city with a high quality of life • an attractive salary according to the Collective Bargaining Agreement for University Staff (level A2) and an organisational retirement plan Application documents (in English): • Letter of motivation • Academic curriculum vitae • education and training (PhD Certificate, PDF) • positions held to date • career breaks (e.g. relevant parental, family or other care periods) • awards and honors • commissions of trust • previous and current cooperation partners • complete list of acquired third-party funding and, if applicable, of inventions/patents • list of most important scientific talks (max. 10) • teaching and mentoring • supervision experience (Master and PhD), if applicable • List of publications • link to your own publicly accessible ORCID record, with a complete and current publication list • three key publications as electronic full text version (PDF, max 30 MB) • Research statement • most important research achievements (max. 2 pages) and planned future research activities (max. 4 pages) • synopsis of three key publications with relevance to the position advertised • publication strategy • Teaching and supervision statement • teaching and supervision concept, including a description of the previous and planned priorities in academic teaching and supervision (max. 2 pages) • teaching evaluations (if available, PDF) If you have any questions, please contact: Only applications submitted through the link "Apply now" below will be considered. The University of Vienna has an anti-discriminatory employment policy and attaches great importance to equal opportunities, the advancement of women and diversity. We place particular emphasis on enhancing women’s representation among the academic and general university staff, particularly in leadership roles, and therefore expressly encourage qualified women to apply. Given equal qualifications, preference will be given to female candidates. University of Vienna. Space for personalities. Since 1365. Application deadline: 09/15/2026 Reference no.: 6003 Tenure Track Professorships https://tt.careers.univie.ac.at/datenabfrage/TT0726CHEM01 Opens in a new tab. Opens in a new tab. Opens in a new tab. × When you visit any website, it may store or retrieve information on your browser, mostly in the form of cookies. Because we respect your right to privacy, you can choose not to allow some types of cookies. 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