Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- Max Planck Institute (MPI) for Psycholinguistics
- Brookhaven Lab
- Heriot Watt University
- KINGS COLLEGE LONDON
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Princeton University
- RCSI - Royal College of Surgeons in Ireland
- Texas A&M University
- Yale University
- ;
- Brookhaven National Laboratory
- CNRS
- Carnegie Mellon University
- Computer Vision Center
- ETH Zürich
- Emory University
- Free University of Berlin
- Harvard University
- Institut Pasteur
- Karolinska Institutet (KI)
- Maastricht University (UM); yesterday published
- Massachusetts Institute of Technology
- Max Planck Institute for Psycholinguistics
- Max Planck Institute for Psycholinguistics; today published
- National Aeronautics and Space Administration (NASA)
- New York University
- Northeastern University
- Reykjavik University
- Stanford University
- Technical University of Denmark
- Universitaetsklinikum Erlangen
- University of Bath
- University of California Irvine
- University of Florida
- University of Nevada Las Vegas
- University of Oxford
- University of Oxford;
- Virginia Tech
- Washington University in St. Louis
- 30 more »
- « less
-
Field
-
About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
-
processes or laws Elicitation of requirements from natural language Applications of declarative specifications (e.g. temporal, modal logics, declarative process models) in the analysis of systems Model-driven
-
. Required Qualifications: Doctoral degree (PhD) conferred by start date Demonstrated experience with analysis of large health databases Training and experience in machine learning and deep learning methods
-
About the role This Research Assistant post will support data collection and analysis on a longitudinal study of children’s pathways through the healthcare system. We are looking to recruit a
-
: Expert on steels and steel welding or additive manufacturing Develop advanced machine learning framework to combine different modality and fields of data Conduct CALPHAD-based simulations in a high
-
, geometric modelling, acoustic signal propagation, Monte Carlo simulation methods, decision theory, uncertainty quantification, machine learning. Applications and areas of key innovation Image analysis
-
simulation methods, decision theory, uncertainty quantification, machine learning. Applications and areas of key innovation Image analysis, computer graphics, autonomous and assisted driving, 3D scene analysis
-
and implementation of data systems and analysis platforms with the platform development team (developers, data managers, scientists) Supporting strategic planning and integration of new data modalities
-
datasets, machine learning, and experimental methods to investigate how the tumor microenvironment and gene regulatory factors control tumor metastasis cascade. By advancing our understanding of malignant
-
computer science using data-driven techniques (graph theory, ICA, machine learning), in other imaging modalities (DTI; MEG), and in multimodal integration will be relevant. Experience with AFNI/SUMA, SPM, FSL