Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
conducive to scientific qualification and provides the opportunity for further academic development. Where to apply Website https://uni-bielefeld.hr4you.org/job/view/4748/research-position-phd-student-m
-
-Doctoral Associate (9546 Post-Doctoral Associate) position. For more info on the division, visit http://www.sph.umn.edu/academics/divisions/biostatistics/. The successful candidate will work with Dr. Thierry
-
impact-based health early warning systems. The successful candidate will join the research team of Dr. Joan Ballester Claramunt (https://www.joanballester.eu/ ) at ISGlobal within the framework
-
Design Lab – works on modelling, control and optimization for mechatronic systems, industrial robots and processes (https://dynamics.ugent.be ). We are part of the department of Electromechanical, Systems
-
the development and application of advanced techniques, including AutoML, Bayesian optimization, neural architecture search, reinforcement learning, and active learning, with the explicit goal of achieving
-
beginning August 2026. Visit https://sc.fsu.edu , for more information. The successful candidate is expected to develop an interdisciplinary research group with a focus on Bayesian inference or inverse
-
investigating how data-efficient and resource-efficient techniques, such as data attribution, data selection/reweighting, data valuation, data curation, Bayesian optimization, active learning, can be applied in
-
models, spatial Bayesian methods, case time series, case crossover. Have experience with the management and analysis of large climate and/or health databases. Have experience with Linux environment and
-
environmental factors such as fluctuating wind speeds and saltwater exposure. Using advanced statistical and machine learning techniques, including Bayesian inference and stochastic modelling, the project will
-
allow brute-force exploration it is important to select the most informative experiments. Bayesian optimization, an iterative global optimization algorithm, has been shown to be a more efficient in