Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
- Computer Science
- Engineering
- Biology
- Medical Sciences
- Science
- Economics
- Materials Science
- Earth Sciences
- Mathematics
- Business
- Chemistry
- Electrical Engineering
- Linguistics
- Environment
- Arts and Literature
- Education
- Law
- Physics
- Philosophy
- Psychology
- Social Sciences
- Sports and Recreation
- 12 more »
- « less
-
Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
to develop machine learning-enabled approaches for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building
-
stem cell models from patients with Parkinson's disease to understand the underlying causes of neurodegeneration and to develop biomarkers and new therapies for Parkinson's disease. http
-
effectiveness. Integrate FDD and maintenance outputs with digital twins, predictive control frameworks, and operator decision support systems within FLARE. Plan, coordinate, and participate in industrial site
-
Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building cutting edge machine learning techniques
-
Lab applies rigorous evaluation and modeling methods, including natural and field experiments, randomized controlled trials, behavioral economics, and machine learning, to help policymakers identify and
-
attention to scientific rigor and interpretability Experience with XAI tools (SHAP, LIME, Integrated Gradients) to identify which features of the model are driving the predictions Clear written and verbal
-
broader portfolio of academic affairs and data science initiatives, including AI integration, predictive modeling, statistical analysis, machine learning, and analytics infrastructure development. A major
-
lightweight deep learning model for welding defect recognition. Weld. World. https://doi.org/10.1007/s40194-024-01759-9 J. Franke, F. Heinrich, R.T. Reisch, “Vision based process monitoring in wire arc additive
-
for control” funded by the EU Partnership on Animal Health and Welfare (EUPAHW, https://www.eupahw.eu/ ). Supervisors Dr Timothée Vergne is an Associate Professor of Veterinary Public Health at the National
-
breeding programs and to support the reduction of methane emissions; a strong interest in statistical models, genomic prediction, and quantitative genetics, preferably with experience with one of more