Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
software engineering practices. Desirable Skills: knowledge of computer vision, Bayesian theory, or signal processing; experience with prototyping, experimentation, or technical evaluation of interactive
-
Is the Job related to staff position within a Research Infrastructure? No Offer Description 2-YEAR POSTDOCTORAL POSITION AVAILABLE AT NEUROSPIN/INM (PARIS, FRANCE) https://computationalbrainteam.com/en
-
of neural networks, information-theoretic and optimal-transport perspectives on representation and generalisation, probabilistic numerics and Bayesian deep learning, and emerging frameworks for scientific
-
Implementing Bayesian networks and uncertainty quantification techniques to account for sensor noise and model confidence limits Designing, training, and fine-tuning computer vision models to extract clinically
-
, optimization, and characterization integrating imaging, experimental metadata, and diffraction outcomes. Design and deploy computer vision methods to detect and track crystal growth. Develop closed-loop
-
baseline data for estimating the effectiveness of proposed restoration measures for species, habitats, and ecosystems. The Positions The selected candidates will work in close collaboration with Dr. Martin
-
to have experience in several of the following areas: data processing, statistical analyses, R software, regression models, process-based models such as DSSAT or APSIM, Bayesian statistical analysis
-
or application. Strong technical expertise in one or more of the following areas: Computer Vision and Image Processing Machine Learning, Deep Learning, and Reinforcement Learning Large Language Models (LLMs) and
-
at the beginning of employment. Position description The successful candidate will work within the research project “Advances in generalized Bayesian inference via differential-geometric methods” funded by
-
the same systematics identified in the observables. d) Estimation of cosmological and “nuisance” parameters using Bayesian methods. 4. The research activities provided for the post-doc assignment will