Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Austria
- France
- United Kingdom
- Germany
- Canada
- Singapore
- Norway
- Belgium
- Netherlands
- Spain
- Australia
- United Arab Emirates
- Sweden
- Luxembourg
- India
- Switzerland
- China
- Denmark
- Finland
- Czech
- Italy
- Morocco
- Poland
- Romania
- South Africa
- Barbados
- Europe
- Hong Kong
- Japan
- New Zealand
- Portugal
- Saudi Arabia
- Worldwide
- 24 more »
- « less
-
Program
-
Field
-
experimental design. Proficiency with machine vision and deep learning techniques, including image segmentation, landmark placement and metric learning, for the automation of phenotypic analysis of large image
-
that preserves object identity or style. They should have a solid publication record in top-tier computer vision conferences such as CVPR, ICCV, or ECCV, and demonstrate proficiency in deep learning frameworks
-
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical
-
, deep learning and AI technologies while anticipating faculty needs and strategically advocating for growth in Princeton-offered services. Responsible for understanding changes to campus need and
-
that shape our future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a
-
. Target start date is January 2026. Appointment Start Date: January 2026 Group or Departmental Website: https://woods.stanford.edu/ (link is external) https://sustainability-accelerator.stanford.edu/ (link
-
future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
-
learning and deep learning methods to analyze multi-omics data (genetic, epigenetic, transcriptomic, imaging, single-cell genomics and spatial omics data) with the goal of understanding the underlying
-
to streamflow as a function of climate and landscape controls, using deep learning and explainable AI Communicate and discuss results with stakeholders to integrate the findings into water management
-
Labor Relations website at https://hr.uw.edu/labor. Qualifications University of Washington postdoctoral scholar appointments are for a temporary, defined period not to exceed five years/60 months