Sort by
Refine Your Search
-
Employer
-
Field
-
of this WASP-financed project is machine learning, in particular dealing with generative models and instabilities associated with cycles of retraining on mixtures of human and machine-generated data
-
and computational modeling to understand complex biological processes. Experience in statistical modeling, machine learning, or analysis of spatial or high-dimensional biological data is considered
-
the research project This project is set to explore so-called shared control between the driver of a car and the car's safety systems. By mechanically disconnecting the driver's steering wheel from
-
, Internet of Things, Systems-of-Systems automation, Machine Learning, Deep Learning, Data Science, Electronic systems design, and sensor systems. Cyber-Physical Systems (CPS) focuses on integrated software
-
methods, including modern machine learning methods, to draw inferences from register data. A third project “Integrative machine and deep learning models for predictive analysis in complex disease areas“ is
-
machine learning techniques into a modern AI planning system. The project will involve both theoretical and experimental work As a PhD student, you devote most of your time to doctoral studies and the
-
or more of the following programming languages/environments: Unity/Unreal, C/C++, C#, Python Basic understanding of the artificial intelligence and machine learning fields. Place of employment: Karlskrona
-
of small cryptic plasmids in the development and spread of antibiotic resistance, and ii) Use machine learning tools to examine the complex interplay between bacterial hosts, various plasmids and resistance
-
well as the clinical activities at the Karolinska University Hospital, unique access to international expertise in machine learning, state-of-the-art imaging, diverse patient cohorts, and relevant computational
-
variability in risk factor susceptibility, treatment response, disease pathogenesis, and clinical diagnosis (biostatistics, machine/deep learning), ii) Investigating causal processes and disease mechanisms