Associate Senior Lecturer (DDLS fellow) in data driven epidemiology and biology of infection
Background
Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the next-generation of data-driven life scientists and to create globally leading computational and data science capabilities in Sweden. The program is funded with a total of 3.1 billion SEK (about 290 MUSD) over 12 years from the Knut and Alice Wallenberg (KAW) Foundation. The DDLS program will recruit 39 high-profile junior group leaders and launch over 210 postdoctoral positions and establish a research school for 260 PhDs, including industry PhDs and postdocs. Fellows will be recruited to the 11 participating host universities/organizations, but brought together under a national DDLS program coordinated by SciLifeLab. The DDLS program has four strategic areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and biology of infection. For more information, please see www.scilifelab.se/data-driven.
During 2022-2024, the two first rounds of 36 junior group leaders joined us as DDLS Fellows, and now we are looking to recruit an additional group. Each DDLS Fellow will receive a recruitment package of 17 MSEK (about 1.6 MUSD) for a 5-year period, covering their own salary and other resources, such as two PhD students and postdoc positions. The Fellow positions are tenure-track with the host organizations assuming responsibility of the long-term faculty appointments following a tenure evaluation.
The future of life science is data-driven. Will you be leading that change with us? Then join us in this unique program!
At Lund University, we are looking to fill the position as DDLS fellow in data driven epidemiology and biology of infection.
Data driven epidemiology and biology of infection covers research that will transform our understanding of pathogens, their interactions with hosts and the environment, and how they are transmitted through populations. Research will have a strong focus on computational analysis or predictive modeling of pathogen biology or host-microbe systems for which multidimensional, genome- scale experimental data are now available or it may use population-scale genetic, clinical, or public health data from pathogen surveillance efforts and biobanks.
The subject area concerns research in the general area of epidemiology and biology of infection with a strong computational profile. This research subject area aims to lead to innovative development and/or application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques.
Lund University foresees that the outcome of the research will contribute to gained knowledge of medical importance, for example understanding of host-pathogen interactions, infection biology including structure-function relationships and transmission of infectious diseases, that could translate into identification of novel targets for therapeutic and prophylactic purposes, as well as tools for infectious disease monitoring and prediction
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