1,338 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" positions at Nature Careers
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Germany
- Austria
- Denmark
- United Kingdom
- France
- Worldwide
- India
- Spain
- Belgium
- Canada
- Sweden
- Mexico
- South Africa
- Hong Kong
- Switzerland
- Luxembourg
- Italy
- Singapore
- United Arab Emirates
- Australia
- Finland
- Netherlands
- Ireland
- Japan
- Poland
- South Korea
- Turkey
- Argentina
- Barbados
- Czech Republic
- Guadeloupe
- Israel
- Norway
- Portugal
- Taiwan
- Vietnam
- 27 more »
- « less
-
Program
-
Field
-
research group “Machine Learning for Biomedical Data” led by Prof. Dominik Heider and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles of Reproduction. The CRC 1748 involves
-
candidates would have direct experience with several of the following methodologies: optogenetics, fiber photometry, in vivo calcium imaging, and/or machine-learning-based behavioral assessment. Additionally
-
on bioinformatics, computational biology, machine learning, Ai, and/or related fields, from applicants committed to translational research applicable to the field of cancer. The DCCB, located at the Health Science
-
Grundstufe (praedoc) Reference no.: 5208 Explore and teach at the University of Vienna, where more than 7,500 academics thrive on curiosity in continuous exploration and help us better understand our world
-
driven, to allow researchers to focus on data intensive tasks. What we provide: An opportunity to broaden research experience in a collaborative environment. A team that believes in continuous learning and
-
collaborative environment. A team that believes in continuous learning and cultivates an environment of collaboration. Collaboration with research labs and other shared resources, including Molecular Genomics
-
collaborative environment. A team that believes in continuous learning and cultivates an environment of collaboration. Once trained, flexible schedule What you’ll do: Operate equipment in the cagewash facility
-
machine learning methods are a plus. Qualifications: PhD in neuroscience, or related fields DeepLabCut or similar methods Demonstrated hands-on experience with 2-photon imaging techniques Experience
-
), proteomics (LC-MS/MS), (epi)genomic data processing, multi-omics integration, machine learning approaches for high-dimensional data, confocal / two-photon imaging, tissue clearing and light-sheet microscopy
-
skills in data science, advanced AI interface development and machine learning?to apply climate change and other relevant data to real-world problems exchange and coordination with project partners Your