Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Harvard University
- Universidade de Coimbra
- INESC ID
- National University of Singapore
- University of Oslo
- City of Hope
- ETH Zurich
- Genentech
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- Medical College of Wisconsin
- Nature Careers
- Simons Foundation/Flatiron Institute
- University of California, San Francisco
- University of Maryland, Baltimore
- University of North Carolina at Chapel Hill
- 5 more »
- « less
-
Field
-
research and travel expenses. Relevant areas of expertise include: algorithms and complexity, natural language processing, and knowledge of the algorithmic fairness literature. The postdoc will be mentored
-
are looking for junior scientists who are especially interested in working at the intersection of systems and algorithmic theory, in areas such as programmable network architectures, data center network
-
are looking for junior scientists who are especially interested in working at the intersection of systems and algorithmic theory, in areas such as programmable network architectures, data center network
-
technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data
-
algorithm development, data analysis and inference, and image analysis Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software
-
experimental cancer biologists to address major scientific problems. The Postdoctoral Fellow will apply existing analytic pipelines and devise new algorithms to explore data derived from multiple DNA sequencing
-
technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data
-
-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
-
by identifying “the right drug for the right patient at the right dose”. The candidate will also work with, and be co-mentored by, exceptional scientists in Human Genetics and Computational Sciences
-
validate predictive algorithms for biomarker discovery Optimize data integration techniques for multi-omics and clinical datasets Perform trend analysis of bacteria-containing samples over time to observe