Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
application to the European mission of a Digital Twin Earth. ML research directions will include physics-aware machine learning, reasoning, uncertainty estimation, Explainable AI, Sparse Labels and
-
application to the European mission of a Digital Twin Earth. ML research directions will include physics-aware machine learning, reasoning, uncertainty estimation, Explainable AI, Sparse Labels and
-
challenges in AI4EO and their application to the European mission of a Digital Twin Earth. ML research directions will include physics-aware machine learning, reasoning, uncertainty estimation, Explainable AI
-
. Applicants should ideally be experienced with qualitative and quantitative social science research methods; interested in working in an interdisciplinary, collaborative research environment; able to carry out
-
atmosphere and possibilities to further extend your qualifications through educational programs within the DFG-funded collaborative research center SFB-TRR 179. The position is available from the December 1st
-
the developed code Publishing the developed approaches in international journals and conferences Requirements Promising applicants have: A master’s degree in Computer Science, Geodesy, or related discipline Very
-
high resolution from big geospatial data Exchange with our scientific partners Publishing the developed approaches in international journals and conferences Requirements Promising applicants have: A
-
. Application We look forward to receiving your application documents (cover letter, curriculum vitae, study certificates, etc.) by e-mail until October 17th, 2021 to apply@lmf.lrg.tum.de. Please add the keyword
-
department at ETH Zurich. Your application should comprise at least: An application letter pointing out why you are interested in our work and a detailed curriculum vitae together with transcripts of grades
-
environment ▪ Full-time position (TV-L E13) with the possibility of earning a doctoral degree or postdoc To apply Please send us your application by e-mail (jobs@lnt.ei.tum.de) with the following documents