Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
optimization of large-scale, multiscale, or networked chemical processes. Special emphasis will be directed toward incorporating advanced algorithms, high-performance computing, uncertainty quantification
-
characterization, and uncertainty calculation. Interest in topics related to gas emissions and the development of reference materials, as well as the ability to work rigorously in a laboratory environment. Must
-
theories from tractable models (probabilistic circuits) and Bayesian statistics to tackle the reliability of machine learning models, touching topics such as uncertainty quantification in large-scale models
-
primary method is the most prevalent due to its cost-effectiveness; however, it necessitates estimating the convective exchanges surrounding the sphere, leading to significant uncertainty. Furthermore
-
/statistics (experimental design, evaluation, uncertainty quantification) Excellent programming skills in Python (C/C++ is a plus); experience with HPC environments (e.g., SLURM) is welcome Interest in
-
of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and uncertainty quantification. The position comes with a
-
materials and their thermo-mechanical behavior; experience with PEEK or polyamides is an advantage. Experience with explainable AI, uncertainty quantification, or physics-informed learning. Familiarity with
-
engineering systems, structural uncertainty quantification, physics-informed learning, data fusion, real-time sensing and control, simulation of cascading failures in interconnected networks, edge intelligence
-
programme Reference Number AE2025-0503 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0503
-
asymptotic analysis of stochastic processes Impact: Faster detection of anomalies and reliable uncertainty quantification Job Description As a PhD candidate in Mathematical Statistics, you will develop novel