Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
interdisciplinary projects integrated into large national and European research consortia such as the DAPHNE (DAta for PHoton and Neutron Experiments) NFDI consortium and the Cluster of Excellence "Machine Learning
-
experiments. For more information, visit our web page www.soft-matter.uni-tuebingen.de We are currently looking for a PhD student to join our team and help us make exciting new advances in applications
-
Moller Institute (MMMI) , at the University of Southern Denmark (SDU) , invites applications for a fully funded PhD position on the topic of automated mapping and identification of large structure
-
provide large and complex datasets. By applying advanced pattern recognition and clustering algorithms, the aim is to automatically detect coherent spatial domains. These domains represent regions with
-
translational research. Machine Learning, Statistical Modeling & Informatics Research Apply ML/AI approaches for pathogenicity prediction, phenotype clustering, or multimodal data modeling. Support translational
-
generated in the scattering experiments. For more information, visit our web page www.soft-matter.uni-tuebingen.de We are currently looking for a PhD student to join our team and help us make exciting new
-
, Computer Science, or related field. Five (5) years of experience in genomic data processing, variant annotation, or large-scale data analysis. Proven leadership in pipeline development, variant
-
well as with Computer Science in general (algorithms and data structures, programming languages, software engineering). In addition, collaborations with the VSC (Vienna Scientific Cluster) and subsequently with
-
emphasize multi-wavelength survey science, the galaxy-halo connection, cluster cosmology, and large-scale cosmological simulations. Analysis efforts cover topics such as CMB power spectra, CMB lensing, galaxy
-
developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health