Computer Science, Second Cycle, Bioinformatics, AI and Network Biology for Precision Medicine and Health
Örebro University
Startdatum:
Slutdatum:
Studietakt: 50 %
Publicerad utbildningskatalog
Utbildningsinformation från den publicerade källan. Utbildningen och dess tidsbundna tillfällen hålls åtskilda.
Kod: DT902A
This course offers an in-depth, hands-on approach to applying computational techniques such as bioinformatics, machine learning, network medicine, and AI to integrate and analyse molecular, clinical, and pre-clinical data. You will learn how to handle diverse types of data – from genomic sequences, molecular data to clinical outcomes – and implement advanced modelling approaches using tools and algorithms that can process such data and find general predictive patterns. Emphasizing practical experience, you will engage in real-world data analysis tasks, either on your own hardware or via online platforms, allowing you to develop technical skills in data integration, predictive modelling, and visualization. In this interdisciplinary course, you will collaborate with students from fields such as biomedicine, biology, chemistry, and other life sciences, gaining experience and insights into how data science can be applied in healthcare. An important focus is on cultivating effective inter-professional communication and collaboration between diverse disciplines, preparing you for collaborative project work in complex, real-world environments.
At least 180 credits, of which at least 60 credits in computer science and 15 credits in math. The applicant must also have qualifications corresponding to the course "English 6" or course "English level 2" from the Swedish Upper Secondary School.
Varje tillfälle har egna datum och villkor. Avslutade tillfällen behålls som historik och innebär inte att en ny ansökan är öppen.
Örebro University
Startdatum:
Slutdatum:
Studietakt: 50 %
Hämtad: .
Publicerad: .
Publiceringsversion: 8e217193-f5fa-4778-b085-a4521fd03e8d
Kontrollsumma: 1b0dc54c0fc8a359f83ba9dc8f9d468479ce432de4c03bce3b8b33dd67fe3f6c
Senast ändrad enligt källan: 2026-01-26T13:44:25