Sort by
Refine Your Search
-
samples, lack of training data and sample variability. In this project we aim to develop AI/ML workflows for improved quantitative analysis of LNPs. Your responsibilities will include optimisation of data
-
regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
-
Uppsala University, Department of Information Technology Are you interested in probability theory, statistics, and mathematical modelling? Would you like to develop new methods for uncertainty
-
of algorithms, machine learning, optimization, scientific software development and high-performance computing. The division is also an important part of the eSSENCE strategic collaboration on e-science and of
-
Are you interested in developing mathematically grounded methods for uncertainty quantification in deep learning, particularly for large language models in healthcare applications? Are you looking
-
application! We are looking for a PhD student in Medical Science, AI and Bioinformatics. Your work assignments This project aims to develop AI foundation models for integrative single-cell and multi-omics
-
advanced technology development to biomedical studies. The main research areas include immuno-oncology, sensitization, and biomarkers. Advanced technologies are utilized within the department, including
-
islet physiology and single-cell genomics to join the lab of Dr. Joan Camuñas. The lab of Dr. Joan Camuñas stands at the interface of genomics, biophysics and precision medicine. Our mission is to develop
-
of the world’s largest research environments in computational science, with large activities in areas such as machine learning, optimization, scientific software development and high-performance computing
-
improvement of existing workflows, while development of new analytical methods is not a primary responsibility of the role. Contract terms Temporary employment until 31 October, 2027. Preferable starting date