Two DDLS fellow positions to KTH

The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) is a 12-year initiative funded with a total of 3,1 billion SEK from the Knut and Alice Wallenberg Foundation. The purpose of the program is to recruit and train the next-generation of data-driven life scientists and to create globally leading computational and data science capabilities in life science in Sweden.

The program will recruit 39 eminent early career group leaders as DDLS Fellows, launch over 210 postdoctoral positions and establish a research school for 260 PhDs, within both academia and industry. The program is coordinated by SciLifeLab, a nationwide research infrastructure and a hub for cross-disciplinary life sciences. The Fellows will be recruited to the 11 participating host universities/organizations, enabling them to link up with strong local research environments as well as with the national DDLS program. The DDLS program promotes collaborative interdisciplinary work and engagement with industry, healthcare and other national and international partners, such as WASP, with the aim of bridging the life science and data science communities.

The DDLS program will focus on four strategic areas of data-driven research: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and infection biology. We are now looking for the first 20 junior group leaders to join us as DDLS Fellows.

Each DDLS Fellow will receive a recruitment package of 17 MSEK, which is meant to cover 5 years of his/her own salary, two PhD students and two postdoc positions, as well as running costs. The Fellow positions are tenure-track, and the universities/organizations will assume the long-term responsibility of their support as tenured faculty.

The future of life science is data-driven. Will you be leading that change with us? Then apply now!

The two DDLS fellow positions

Assistant professor in data-driven cell and molecular biology

Subject field

Data-driven cell and molecular biology

Subject description

The subject area concerns 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. This research should lead to the development or application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques to analyze, integrate and make sense of cell and molecular data. 

A specific focus is the development of methods that take a quantitative approach to cell and molecular biology with potential to give new insights of biophysical relevance. These methods can be applied to data generated by, but not limited to, microscopy and simulation techniques that are currently developed at KTH and SciLifeLab, including single cell screening, super-resolution fluorescence microscopy, cryo-electron microscopy, and molecular dynamics simulations.

Duties

The employment includes research and teaching in the subject area. The assistant professor is expected to apply for research funding, as well as creating new collaborations within and outside KTH. The assistant professor is also expected to teach at basic level, advanced level and postgraduate level, and develop existing and new courses. In addition, it is expected that the assistant professor contributes to the development and teaching of subject-specific courses and supervision of degree projects and doctoral students in the subject area. Some administrative tasks are also included. The assistant professor is expected to be able to teach in Swedish within four years. If necessary, a language plan will be drawn up at the start of employment.

The assistant professor will be given opportunity to develop their independence as researcher and gain accreditation that may allow them to take other teaching positions with higher eligibility requirements (see Chapter 4, Section 12 a of the Higher Education Ordinance). Following application, the assistant professor can apply for promotion to associate professor in accordance with Chapter 4, Section 12 c of the Higher Education Ordinance.

Learn more and apply

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Assistant professor in Data-driven Precision Medicine and Diagnostics

Subject field

Data-Driven Precision Medicine and Diagnostics.

Subject description

The subject concerns data-driven research on precision medicine, such as the use of computational tools to integrate molecular and clinical data for translational research and diagnostic development thereby facilitating individualized patient care. Data integration and analysis can be used for patient stratification, for discovery of diagnostic biomarkers and for longitudinal monitoring and follow-up. Precision medicine also depends on capabilities for data interpretation, visualization and clinical decision support. The research is expected to use assets, such as electronic health care records, molecular data (e.g. imaging and omics), or longitudinal patient and population registries, biobanks and digital monitoring data.

This includes development and use of system biology methods and/or pharmacological modelling to develop precision treatment, including precision dosing of drugs and experimental validation.

Duties

The position is intended for research, supervision of PhD students, and PostDocs, and teaching on basic level, advanced level, and research level. The assistant professor is expected to develop courses in the subject field and teach courses given today by the School of Engineering Sciences for Chemistry, Biotechnology and Health.

The assistant professor will be given opportunity to develop their independence as researcher and gain accreditation that may allow them to take other teaching positions with higher eligibility requirements (see Chapter 4, Section 12 a of the Higher Education Ordinance). Following application, the assistant professor can apply for promotion to associate professor in accordance with Chapter 4, Section 12 c of the Higher Education Ordinance.

Learn more and apply

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