Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Luxembourg
- CNRS
- French National Institute for Health Research (INSERM)
- Institut Pasteur
- 3IA Côte d'Azur
- CEA
- Luxembourg Institute of Health (LIH)
- DI ENS
- European Magnetism Association EMA
- IMT Mines Ales
- INSERM
- IRCM - Cancer Research Institute of Montpellier
- Inria, the French national research institute for the digital sciences
- Télécom Paris
- Universite de Montpellier
- University of London;
- University of Toulouse
- 7 more »
- « less
-
Field
-
vision frameworks, applied machine learning techniques, and medical imaging standards Develop user-friendly front-end interfaces, web dashboards, or software demonstrators to make biomedical image analysis
-
and machine learning–based analysis. Behavioral features are compared at inter- and intra-disease levels to identify disease-specific signatures and establish a foundation for future circuit-level
-
-career scientist to develop cutting-edge machine learning approaches for understanding and designing pathogen antigens. This is a unique opportunity to help shape a new research program at the intersection
-
French National Institute for Health Research (INSERM) | Lille, Nord Pas de Calais | France | 2 months ago
bioinformatics workflows in Python for the analysis of transcriptomic, proteomic, single-cell transcriptomic, and interactome datasets. Design and implement Big Data and machine learning approaches using Python, R
-
IRCM - Cancer Research Institute of Montpellier | Montpellier, Languedoc Roussillon | France | 3 months ago
, Computer Vision, AI, Medical Imaging, or a related discipline. ● At least 3 years of research experience (post-PhD), ideally in an academic or public research setting. ● Solid grasp of deep learning theory
-
in the field of operational research and/or machine learning algorithms would be a plus. In accordance with the commitments made by the CEA to promote the integration of disabled people, this job is
-
programming, e.g. Python or MATLAB, and an interest in concepts from reservoir computing or machine learning, is welcome A genuine interest in interdisciplinary research at the interface of biology, engineering
-
pipelines, as well as developing new algorithms and data-processing routines. This relates also to new methods such as wearables, markerless motion capture, machine and deep learning (ML/DL) and artificial
-
of analysis pipelines Development, maintenance and application of programming scripts for omics data analysis and creation of network and machine learning models Data integration support for analysis pipelines
-
measurement methods. These procedures target the assessment of steel properties for reuse in a new construction. Besides experimental work in the laboratory, machine learning will be employed to develop