Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Technical University of Munich
- Cranfield University
- Technical University of Denmark
- ; City St George’s, University of London
- Forschungszentrum Jülich
- KINGS COLLEGE LONDON
- Leiden University
- Nature Careers
- UNIVERSIDAD POLITECNICA DE MADRID
- CWI
- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); yesterday published
- Leibniz
- Leiden University; today published
- Linköping University
- McGill University
- Medizinische Universitaet Wien
- NTNU - Norwegian University of Science and Technology
- Reykjavik University
- University of Basel
- University of Nottingham
- University of Nottingham;
- University of Southern Queensland
- University of Twente (UT)
- University of Tübingen
- 15 more »
- « less
-
Field
-
Research: Visual Exploration and AI Prediction Modeling of Real-Life, Multi-Modal Data” as a PhD-Position in machine learning. You will work alongside leading experts at the Computational Imaging Research
-
), técnicas y herramientas software de análisis de datos, machine/deep learning (Pandas, SHAP, TensorFlow, etc.) y específicas de análisis de imágenes, estadística, simulación, entornos cloud (tipo Kubernetes
-
adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural data to decode multisensory information Investigate how neural
-
[maps] and the TUM Garching campus [maps], and all members are affiliated with both institutes. As a PhD candidate in our group, you will drive your own research on machine learning methods in close
-
. The successful candidate will develop advanced skills in multi-modal sensor fusion, signal processing, machine learning, and integrity assessment, as well as transferable abilities in critical thinking, project
-
from visual and auditory cortices recorded over multiple days Apply and adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural
-
, or willingness to work with them Experience with multi-modal machine learning methods Familiarity with formal linguistics, particularly formal semantics and pragmatics We encourage applications from individuals
-
undermine this future. Can you see how Machine Learning, Computer Vision, and Robotics can open up opportunities for autonomously operating agricultural robots? Are you passionate about making agriculture
-
generative models, geometric machine learning, dynamical systems, and/or multi-modal learning. From the materials science perspective, our primary focus will be on ultra-thin, so-called, 2-dimensional
-
strengthen the data science and machine learning activities of the IAS-9 with exciting new topics. You will work in a multidisciplinary team of enthusiastic data scientists, software developers and domain