Postdoc in bioinformatics and integrative omics
School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH
KTH Royal Institute of Technology in Stockholm has grown to become one of Europe’s leading technical and engineering universities, as well as a key centre of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as architecture, industrial management, urban planning, history and philosophy.
The group of Integrative Omics and Precision Medicine is headed by Professor Mathias Uhlén and is located at SciLifeLab Stockholm. The main project of this group is the Human Protein Atlas project, where a combination of genomics, transcriptomics, proteomics and antibody-based profiling is used to study the global protein expression patterns in human cells, tissues and organs. The above-mentioned collaboration between WASP and DDLS will be performed in the context of an interdisciplinary research project entitled “Visual Analytics for Enhancing Quality and Trust in Genome-wide Expression Clustering and Annotation”, where the Systems Biology group at the Royal Institute of Technology (KTH) and the Information Visualization group at Linköping University (LiU), headed by Professor Andreas Kerren, work closely together.
There is a need for a functional genome-wide annotation of the protein-coding genes to get a deeper understanding of mammalian biology. The new data-driven strategy to be developed in the project is based on interpretable unsupervised learning (e.g., dimensionality reduction and clustering) of whole-body co-expression patterns, supported by state-of-the-art visual analytics. Interactive guiding of the clustering process will be used to explore the gene expression landscape in humans and other mammalian species, and to create a whole-body map of all protein-coding genes in all major cell types, tissues and organs. This will allow for the improvement of the quality of the classification of all protein-coding genes according to their whole-body co-expression patterns, resulting in every gene being annotated to a unique expression cluster together with other genes with a similar body-wide pattern.
The focus of this advertised Postdoc position at KTH will be on research and development of an interactive and interpretable clustering strategy to reach these goals and perform analyses of large-scale biological data. The position includes participation in the research group’s work in the Division of Systems Biology at the Department of Protein Science, KTH Solna campus and SciLifeLab. This includes the development of research networks, further development of your own scientific skills and independence, and active participation in education at all levels.
This position is part of a joint collaboration between the two largest research programs in Sweden, the Wallenberg AI, Autonomous Systems and Software Program (WASP) and the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), with the ultimate goal of solving ground-breaking research questions across disciplines.
The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) is a 12-year initiative that focuses on data-driven research, within fields essential for improving the people´s lives, detecting and treating diseases, protecting biodiversity and creating sustainability. The programme will train the next generation of life scientists and create a strong computational and data science base. The program aims to strengthen national collaborations between universities, bridge the research communities of life sciences and data sciences, and create partnerships with industry, healthcare and other national and international actors. Read more: https://www.scilifelab.se/data-driven
Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish industry. Read more: https://wasp-sweden.org/
What we offer
- A position at a leading technical university that generates knowledge and skills for a sustainable future
- Engaged and ambitious colleagues along with a creative, international and dynamic working environment
- Works in Stockholm, in close proximity to nature
- Help to relocate and be settled in Sweden and at KTH
- A doctoral degree in bioinformatics, biostatistics, biotechnology, computational biology, or a related field (or an equivalent foreign degree), obtained within the last three years prior to the application deadline (With some exceptions for special reasons such as periods of sick or parental leave, kindly indicate if such reason exists in your resume).
- A strong background in bioinformatics, computer science, computational biology or equivalent with a profound knowledge about biology and biostatistics.
- Good knowledge and experience in methods for clustering and dimensionality reduction
- Documented experience in management, visualization, analysis and integration of large-scale biological datasets. Solid foundation in the fundamentals of biostatistics and multivariate data analysis.
- Knowledge of architecture and tools for managing and integrating omics data including statistical analysis methods and bioinformatics tools, packages, algorithms, and databases.
- Advanced skills in a high-level programming language, preferably R, Python or Perl, as well as experience with Unix/Linux environment. Excellent skills in English, both written and spoken.
- Research expertise
- Experience in analysis of transcriptomics data is meriting
- Scientific skills
- Educational ability
- Collaborative abilities
- Well-developed analytical and problem-solving skills
- Structured working style
- Awareness of diversity and equal opportunity issues, with specific focus on gender equality
Great emphasis will be placed on personal competency.