Sort by
Refine Your Search
-
Category
-
Program
-
Employer
- Chalmers University of Technology
- SciLifeLab
- KTH Royal Institute of Technology
- Umeå University
- University of Lund
- Jönköping University
- Karolinska Institutet (KI)
- Karolinska Institutet, doctoral positions
- Lunds universitet
- Umeå universitet stipendiemodul
- Uppsala University
- Uppsala universitet
- universitypositions
- 3 more »
- « less
-
Field
-
programme in question, the following are considered as other qualifications: Strong foundations in Machine learning and reinformement learning. Cloud computing and cloud technology. Low-level programming and
-
candidates whose expertise falls within one or more of the following areas: computational and mathematical modeling, statistical modeling, machine learning, network science, bioinformatics, applied mathematics
-
, Cybersecurity, AI, Machine Learning (ML), Data Science, or another closely related subject, no more than three years before the application deadline; has documented knowledge of AI and ML; has demonstrated
-
, drawing on machine learning where it strengthens these methods. The research supports mission-critical scenarios and feeds into an end-to-end resilience proof of concept developed together with Swedish and
-
nutrition, such as: analysis of time series data and dynamic processes, where signals and responses evolve over time. statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and
-
domains such as telecom, defence and cloud. You will join the Machine-Intelligence for Networks and Distributed Systems (MINDS) research group at the Department of Computing and Learning Systems, School
-
data and multimodal datasets combining imaging and molecular measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with
-
description Work on EU projects to develop next‑generation transport, emission and health forecasting models by integrating deep learning, xAI, and diverse data sources such as traffic sensors, smart‑card data
-
. The following experience will strengthen your application: industrial product development or manufacturing research modelling and simulation, digital twins or digital threads AI, machine learning
-
, drawing on machine learning where it strengthens these methods. The research supports mission-critical scenarios and feeds into an end-to-end resilience proof of concept developed together with Swedish and