Sort by
Refine Your Search
-
Listed
-
Employer
- University of Lund
- Chalmers University of Technology
- Chalmers tekniska högskola
- Lunds universitet
- SciLifeLab
- chalmers tekniska högskola
- KTH Royal Institute of Technology
- Linköping university
- Linköpings University
- Nature Careers
- Sveriges Lantrbruksuniversitet
- Umeå University
- Uppsala universitet
- 3 more »
- « less
-
Field
-
learning and its application within the Data Science & AI division (DSAI). With 30+ nationalities and strong industry/academic ties, we offer a dynamic, collaborative ecosystem. The AI and Machine Learning
-
using genetic data from family-based studies as well as -omics data for integrative deconvolution and machine learning methods for prognosis and therapeutic biomarker development. The collaborative
-
The postdoctoral researcher will work with computer-based analytical methods and large databases to develop theory and methodology for utilising aggregated data from archaeology, genetics, and linguistics, thereby
-
description and working tasks The project will develop privacy-aware machine learning (ML) models. We focus on data-driven models for complex and temporal data, including those built from synthetic sources
-
environment for all employees through mutual respect and tolerance. Description of the project The postdoc will leverage existing high-throughput data from large scale cohorts and large family cohorts
-
you can say yes to some of the points below, it is highly beneficial: Proficiency in programming languages, preferably Python. Capable of analyzing large datasets Knowledge of AI and machine learning
-
analysis, statistical modelling, linear mixed models, and machine learning among others. The position is well suited for an individual interested in quantitative genetics and data analysis that wishes
-
experience with machine learning techniques in general and neural networks in particular will be highly beneficial. About the employment The employment is a temporary position of 2 years according to central
-
Observation data analysis. You are fluent in Python and have solid experience with relevant machine learning and geospatial libraries such as PyTorch, TensorFlow, GDAL, rasterio, and zarr. You have experience
-
the Division of Data Science and Artificial Intelligence and the employment is with Chalmers University of Technology. The division’s research spans from foundational machine learning theory to applications