Sort by
Refine Your Search
-
Category
-
Program
-
Employer
-
Field
-
models of steel structures with emphasis on fatigue hot-spot modelling, building on existing in-house methods Load and stress estimation using virtual sensing techniques (e.g., Kalman Filters) combined
-
models of steel structures with emphasis on fatigue hot-spot modelling, building on existing in-house methods Load and stress estimation using virtual sensing techniques (e.g., Kalman Filters) combined
-
statistics have been a key element in your work. Experience with data handling and flexibility in using a wide range of statistical methodologies, both frequentist and Bayesian. Demonstrated proficiency in
-
circuit models and algorithms for estimating the charge, health, and power based on direct methods (e.g. open circuit voltage), model-based methods (e.g. Kalman filtering), data driven methods (e.g. machine
-
statistics have been a key element in your work. Experience with data handling and flexibility in using a wide range of statistical methodologies, both frequentist and Bayesian. Demonstrated proficiency in
-
carbon, nitrogen, and water flows in agroecosystems. A solid background in uncertainty quantification, applied statistics, Bayesian calibration, and Monte Carlo simulations. Strong skills in scientific
-
degree in computer science, mathematics, statistics, physics or relevant fields. Strong background in machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph
-
on developing and studying privacy-preserving methods, such as differential privacy, Bayesian privacy, federated learning and synthetic data. The aim is to enable meaningful analyses, such as identifying disease
-
informative but also pose significant privacy risks. Your work will focus on developing and studying privacy-preserving methods, such as differential privacy, Bayesian privacy, federated learning and synthetic
-
Two DTU Tenure Track Assistant Professors in Autonomous Modelling and in Robotic Synthesis of Ene...
) closed-loop materials discovery, e.g., Bayesian Optimization, autonomous analysis of patterns, spectral data or cell-level testing. Experience with predictive control of the synthesis robotics and reaction