Within the Horizon 2020 Framework the wbk Institute for Production Science at the Karlsruhe Institute of Technology (KIT) is looking for three excellent predoctoral research assistants to work in the DIGIMAN4.0 Project:
ESR for intelligent quality control cycles in Industry 4.0 process chains enabled by machine learning (application deadline 31/08/2019)
ESR for Cloud-based automated negotiation mechanism for Supply Chain 4.0 horizontal integration (application deadline 31/08/2019)
The DIGIMAN4.0 (DIGItal MANufacturing Technologies for Zero-defect Industry 4.0 Production) Project aims, within the framework of the MSCA-ITN-2018 initiative, at the provision of world excellent research training to 15 ESRs (Early Stage Researchers) in the field of digital manufacturing technologies for Industry 4.0.
This research training will focus on three main aspects:
At the time of recruitment, the researcher (ESR) must not have resided or carried out his/her main activity (work, studies, etc.) in Germany for more than 12 months in the 3 years immediately prior to his/her recruitment under the project (estimated July 2019). Eligible candidates must be, at the time of the recruitment, in the first four years of their research career and have not been awarded a doctoral degree.
Furthermore, the Applicant must have excellent German and English Skills
Skills and Qualification
The KIT attaches great importance to the professional equality of women and men. We are therefore particularly pleased to receive applications from women. Severely handicapped applicants will be given preferential consideration if they are qualified.Mehr
|Titel||Multiple positions for Industry 4.0 Production at the wbk Institute of Production Science (predoctoral research assistant)|
|Employer||Karlsruher Institut für Technologie (KIT)|
|Job location||Kaiserstraße 12, 76131 Karlsruhe|
|Veröffentlicht||Juli 12, 2019|
|Bewerbungsschluss||August 31, 2019|
|Jobart||PhD/ Doktorand/in  |
|Fachbereiche||Wirtschaftsingenieurwesen,   Künstliche Intelligenz,   Datenverarbeitung in den Bereichen Mathematik, Naturwissenschaften, Ingenieurwesen und Medizin,   Fertigungstechnik,   Maschinenbau,   Wissenschaftliches Rechnen,   Computergestützte Ingenieurswissenschaft,   Big Data,   Maschinelles Lernen,   |