Based on its Structure and Development Plan 2018-2022 "Bioeconomy and Digital Transformation", the University of Hohenheim currently seeks to expand its competence in informatics. Amongst others, this is accomplished by the establishment of the professorships "Bioinformatics", "Food Informatics", and "Artificial Intelligence in Agricultural Engineering" as well as the establishment of the cross-faculty "Computational Science Lab". In addition, the Faculty of Agricultural Sciences is seeking to fill at the earliest convenience the following professorship at the Institute of Farm Management for the first time:
The professorship is funded by the joint program of German federal and state governments for the promotion of early career researchers. This is a grade W1-professorship for which recruitment payments can be offered.
The successful candidate is expected to cover novel aspects of computational sciences that have gained significance as part of the ongoing digitalization in bioeconomy, agriculture, and agribusiness. Focus areas should include data management as well as business and inter-business process optimization. For example, the analysis of mass data ("Data Fusion" and "Big Data Technologies") and data management (Workflows for high-dimensional databases) or the combination of sensor technology and process optimization ("Digital Farming") would be possible. Close cooperation with the Departments of Information Systems in the Faculty of Business, Economics and Social Sciences as well as with the professorship "Food Informatics", which is currently also being filled, is desired.
Teaching will include basic-level courses in data modeling, database management, and software engineering as well as advanced courses within the newly established "Computational Science Lab" at the University of Hohenheim. The candidate should be able to teach both in German and in English. The teaching load will comprise four contact hours per week.
The position offers attractive conditions for tenure-track appointees. This professorship is particularly suitable for highly qualified early career researchers. The requirements for an appointment are a completed university degree, pedagogical suitability and a doctorate of outstanding quality.
If the requirements for civil service are met, the appointment will be a temporary civil service position for six years. After six years, the applicant may be appointed to a W3-position if the requirements described in the University’s quality assurance guidelines are met. The appointment to a W3-position may be done without any additional call for applications and through a simplified appointment process. More information on quality assurance and evaluation is available at https://www.unihohenheim.de/en/appointment-principles.
With equal qualifications, preference will be given to candidates with disabilities.
The University of Hohenheim seeks to increase the proportion of women in research and teaching and therefore strongly encourages female scientists to apply.
Please attach the following documents to your application: a cover letter, a statement of your future research interests, a curriculum vitae, transcripts of records and degree certificates, a list of publications, a list of third-party funded projects, a teaching record, information on teaching evaluations as well as three key publications.
University of Hohenheim
Faculty of Agricultural Sciences (300)
|Intitulé||Tenure Track Professor (W1) of Information Systems in Agribusiness|
|Employer||University of Hohenheim|
|Job location||Universität Hohenheim, 70593 Stuttgart|
|Publié||avril 18, 2019|
|Date limite d'inscription||mai 30, 2019|
|Types d'emploi||Professeur,   Tenure Track  |
|Domaines de recherche :||Science de l'environnement,   Sciences de l'information,   Agronomie,   Science de l'eau,   Sylviculture,   Science alimentaire,   Économie agricole,   Aquaculture,   Science agronomique,    and 8 more. Horticulture,   Fertilisation des plantes, nutrition humaine et animale,   Protection des plantes et santé animale,   Science du sol,   Gestion des déchets,   Science animale,   Économie d'entreprise,   Big Data  |