Sort by
Refine Your Search
-
Country
-
Employer
- Technical University of Munich
- Institute of Computer Science of the Czech Academy of Sciences
- Canadian Association for Neuroscience
- Harvard University
- INESC TEC
- INSERM
- Luleå University of Technology
- Luxembourg Institute of Socio-Economic Research (LISER)
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Nature Careers
- The University of Copenhagen
- University of Canterbury
- 2 more »
- « less
-
Field
-
06.12.2021, Wissenschaftliches Personal The professorship of Data Science in Earth Observation is seeking six new PhD candidates/PostDocs for its new center for Machine Learning in Earth Observation
-
theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
-
Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 17 days ago
. Helmut Grubmüller) is inviting applications for a PhD Student or Postdoc (f/m/d) for the project “Theory and algorithms for structure determination from single molecule x-ray scattering images”. Project
-
on analysing modern and historical textual records through the lenses of graph-network analysis, statistics and machine learning. The topics include: * Topic: Networks in Historical Scholarly/Philosophical
-
. Applicants should: Hold a PhD; with the exception of Research assistant and Graduate student positions. Have a strong background in the fields related to machine learning and artificial intelligence
-
challenges in urban development. You will explore exciting areas such as applying machine learning models to analyze urban mobility patterns, identifying gaps in transport accessibility, and supporting
-
methodologies for analysing RNA modification readouts from large transcriptomic datasets. This position will focus on developing probabilistic deep learning frameworks to identify molecular determinants
-
complexity persist. With the development of optimized array designs and AI-driven methodologies, this research aims to explore the principles of array signal processing and machine learning to enable the next
-
machine learning approaches, and genetic approaches to manipulate the expression of candidate genes in microglia in vivo. The project capitalizes on a cell-therapy recently developed in the team, which
-
motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service