Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- SciLifeLab
- University of Lund
- Linköping University
- Lunds universitet
- KTH Royal Institute of Technology
- Karlstads universitet
- Chalmers tekniska högskola
- Karlstad University
- Nature Careers
- Stockholms universitet
- Umeå University
- Kungliga Tekniska högskolan
- Mälardalen University
- Uppsala universitet
- Blekinge Institute of Technology
- Chalmers Tekniska Högskola AB
- Jönköping University
- KTH
- Lund University
- Stockholm University
- Swedish University of Agricultural Sciences
- chalmers tekniska högskola
- 13 more »
- « less
-
Field
-
with researchers at Chalmers and the University of Gothenburg. You will explore how Bayesian methods can enable risk-aware, real-time trajectory planning and contribute to the development of autonomous
-
understanding of statistics (e.g., hypothesis testing, Bayesian statistics) Good collaborative abilities, independence, and critical thinking. Preferred qualifications In-depth experience with LLM agents
-
description Third-cycle subject: Applied and computational mathematics The Department of Mathematics at KTH is announcing a PhD position in Mathematics with a specialization in AI, focusing on Bayesian inverse
-
modeling, differential equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods. Please read more about the position
-
of Applied Mathematics and Statistics we conduct research within the theory and implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale
-
of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods
-
of Applied Mathematics and Statistics we conduct research within the theory and implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale
-
Mathematics and Statistics we conduct research within the theory and implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational
-
version control and containerization (Docker/Singularity) Statistical Modeling: Quantitative data analysis using GLMs, Bayesian methods, or mixed-effect models to interpret complex perturbation datasets
-
the infrastructure. This role is crucial to ensure that strategic objectives are translated into effective implementation across all activities involving our partners and users. Mimer offer access to AI-optimised