Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
one or more courses at the department each year. You can find more information about us on the Department of Information Technology website . The project will be led by Professor Nataša Sladoje , within
-
are looking for an Industrial PhD Student to join an ambitious project focused on building foundational models of human biology using large-scale, multimodal data. In this role, you will work at the
-
data-driven diagnostics. About the project Cancer treatment often involves surgery, chemotherapy, and radiotherapy. While these treatments have improved outcomes, they can be long-lasting and cause
-
advanced AI and bioinformatics approaches to large-scale single-cell and multi-omics datasets. The project will focus on integrating these data to investigate cellular and tissue-specific signalling
-
, longitudinal patient and population registries and biobanks. Project description Large language models (LLMs) enable the extraction of clinical information from unstructured medical text. However, current LLM
-
The University of Gothenburg tackles society’s challenges with diverse knowledge. 58 000 students and 6800 employees make the university a large and inspiring place to work and study. Strong
-
insights on long-standing questions on sex chromosome evolution and on evolutionary processes at large. Duties In this PhD project, you will explore some of the most fascinating questions in evolutionary
-
data with computational modeling Programming skills in Python, R, or another relevant language. Interest in machine learning, statistical modeling, structural bioinformatics, or analysis of large-scale
-
by developing data-driven approaches to identify and prioritize isoform-specific therapeutic targets, enabling a new level of precision in RNA-based treatments. The project will combine large-scale
-
, DNA–protein conjugation, cell culture, high-throughput sequencing and bioinformatics. During the doctoral education the student will design and run experiments, analyse and interpret data. We value