The Department of Gene Technology, at KTH Royal Institute of Technology, is looking to fill a position as Assistant Professor focused on innovative development and application of computational methods for analysis of cellular and molecular biology data.
The host institution, The Department of Gene Technology, is the most prominent research environment at KTH, according to bibliometrics of the recent years, with pioneering research in the life sciences and extensive national and international collaborations. The Assistant Professor will be a key player in this dynamic research environment located at SciLifeLab in Stockholm, in direct connection with NGI Stockholm.
Description of the DDLS Fellows program
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), coordinated by SciLifeLab, 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 3.3 billion SEK (about 350 MUSD) over 12 years from the Knut and Alice Wallenberg (KAW) Foundation.
The DDLS program funds 50 high-profile young group leaders (“Fellows”), over 210 postdoctoral positions and has established a research school for 260 PhDs, including industry PhDs and postdocs. Fellows are recruited to the 11 participating host universities/organizations, but brought together under the DDLS program, which 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 first and second round of 39 Fellows joined and now we are looking to recruit an additional group of 11 Fellows. 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 salaries for PhD students and postdoc positions. The Fellowships are tenure-track positions with the host organizations, which assume the responsibility for the long-term faculty appointments following a tenure evaluation.
The future of life science is data-driven. Will you be leading the change with us? Then join us in this unique program!
Subject description
At the Department of Gene Technology, at KTH Royal Institute of Technology, we are looking to fill the position as DDLS fellow in Data driven cell and molecular biology.
Data driven cell and molecular biology covers research that fundamentally transforms our knowledge about how cells function by peering into their molecular components in time and space, from single molecules to native tissue environments. The applicant is expected to have a strong computational focus on innovative development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques.
The specific focus is on development and application of methods for analysis of cellular and molecular biology data, primarily omics data, such as bulk and single-cell data, spatially resolved data and mass spectrometry data, but also image and phenotype data or epigenetic data.
The goal is both to develop new computational methods for analysis of data from existing experimental methods, and to develop computational methods that lay the ground for novel experimental techniques for producing omics data.
Duties
The duties include creating a research activity of highest international standard within the subject field, to develop and strengthen the department’s activities within method development for machine learning-based computational biology.
The duties include supervision of PhD students and postdocs, and teaching at basic, advanced and research level. The Assistant Professor is expected to contribute to teaching and program and course development in bioinformatics, data visualization, machine learning, biological statistics, and statistical and computational modeling of biological systems.
Application
For complete information about application procedure and assessment criteria, and to apply, see link to application: