Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
on performance and project needs. **Qualifications** • For Doctoral Candidates: Master’s degree in Computer Science, Information Systems, or Mathematics. **Applicants must demonstrate:** • An excellent academic
-
at the interface of data science and the scientific domains pursued at the three participating Helmholtz centers. Methodologically, a broad range of topics is covered, from large-scale data management to data mining
-
of Prof. Dr. Frank Cichos and Dr. Nico Scherf (Max Planck Institute for Human Cognition and Brain Sciences). The position is part of a collaborative project in the Center for Scalable Data Analytics and
-
of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
-
cells from different mouse models with accelerated aging phenotype. The work of the PhD candidate will include data mining and integration of these datasets with resulting identification of candidate
-
the official DAAD template [doc-Datei] and ask your professors to email the confidential document to the GSPoL (admissions.gspol at uni-muenster.de ). Step 2: personal interview at the GSPoL Step 3
-
with shallow water equations). Python coding for workflow control, data pre- and post-processing as well as model calibration and validation. High-performance computing (HPC) for running test cases and
-
within the Institute of Theoretical Computer Science at TU Dresden. The main research area is the design and analysis of algorithms and data structures, with possible focus areas including randomized
-
17Zipcode37077CityGöttingen Contact details Tel:+49 551 5176-100 E-Mail: golestanian-office at ds.mpg.de Web: https://www.ds.mpg.de/lmp Legal notice: The information on this website is provided to the DAAD by third parties
-
field • Is fluent in English • Is interested in finding innovative, creative solutions • Has good programming/data analysis skills • Is experienced or at least strongly interested in one