Data Science
ILF spans ‘from molecule to human’ encompassing interdisciplinary drug related research data. ILF has strong opportunities to leverage big data sciences within multiple research areas: in silico modelling of drug effects, receptor pharmacology, in vivo animal experiments, ex vivo studies on human tissue, and observational epidemiological studies on drug effects in humans.
Based on ILF strategic goals 2020-2023, we aim at unleashing the full research potential of the Department as well as the individual employee by establishing strong interdisciplinary research clusters supported by core teams with particular focus on data science and innovation respectively.
The Data Science Core Team will:
• Synergize strong drug-related research with strengthening of big data science.
• Establish infrastructure and support for swift integration of big datasets from ILF and public resources.
• Tailor big data into existing and new courses to fill an educational need of the life science industries
• Increase the accessibility of data science expertise and resources to scientists.
• Profile our research data e.g. via online research hubs developed at the Department
• Complete the integration of databases with person-sensitive information and allow linkage in secure environments, e.g. Statistics Denmark, the Danish Health Data Authority and Computerome
Core members
The members in the Data Science Core Team has been appointed based upon their competences within data science.
| Name | Title | Phone | |
|---|---|---|---|
| Andersen, Morten | Professor | +45 353-33506 | |
| Frydenvang, Karla Andrea | Associate professor | +45 353-36207 | |
| Gajhede, Michael | Professor | +45 353-36407 | |
| Gloriam, David E. | Professor | +45 353-36162 | |
| Johansen, Tommy Nørskov | Associate professor, head of studies | +45 353-36412 | |
| Kongstad, Kenneth Thermann | Assistant professor, tenure track | +45 353-36411 |