Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Munich
- DAAD
- Forschungszentrum Jülich
- Nature Careers
- Justus Liebig University Giessen •
- Leibniz
- Academic Europe
- Deutsche Bundesbank
- Deutsches Elektronen-Synchrotron DESY •
- FBN Dummerstorf
- GFZ Helmholtz-Zentrum für Geoforschung
- Heidelberg University
- Max Planck Institute for Software Systems •
- Saarland University •
- University of Göttingen •
- University of Hamburg •
- University of Potsdam •
- University of Siegen
- University of Stuttgart
- University of Würzburg
- Universität Siegen
- 11 more »
- « less
-
Field
-
/software. Contribute to designing and evaluating scheduling algorithms for virtualized or distributed AI resources under varying load, latency, and failure conditions. Build and test a scenario generator for
-
management, in writing styles and techniques, in the handling of software tools for publishing, and managing bibliographies. PDF Download International elements International guest lecturers Projects with
-
cytometry is an advantage Confident handling of Microsoft Office (Excel, PowerPoint, etc.) and image processing software (e.g. ImageJ, Imaris) Willingness to perform animal experiments; experience and FELASA
-
edge AI hardware/software. Contribute to designing and evaluating scheduling algorithms for virtualized or distributed AI resources under varying load, latency, and failure conditions. Build and test a
-
: Fail safe, Distributed Digital Twin for Innovative Air Mobility (IAM) Operations Supervisor: Prof. Dr. Uwe Assmann, Chair of Software Technology and co-supervised by at least one
-
microscopy, microscopy, light sheet fluorescence microscopy) and flow cytometry is an advantage Confident handling of Microsoft Office (Excel, PowerPoint, etc.) and image processing software (e.g. ImageJ
-
- Familiarity with data visualisation software (e.g. Tableau, R-Shiny) would be an asset - Strong analytical skills - Organisational skills as well as the ability to work both independently and as part of a team
-
neuroscience is essential Experience with modelling, analysis of complex dynamical systems, simulation, analysis of large-scale datasets with machine learning methods, and software development are beneficial
-
(compulsory) Lecture series Expert courses Summer schools Soft skills courses Training in scientific programming and statistic software Project management, computer literacy Presentation, communication Writing
-
skills (Python, R, Java, …) and interest to work in polyglot software environments Practical experience with machine learning and AI methods and an interest to learn, adapt and apply ML methods