PostDoc position in genomics/computational biology/bioinformatics
The research group
The Kutter lab has a track record in deciphering molecular mechanism by which noncoding RNAs (i.e. long noncoding, transfer and small RNA) regulate genes and genome structure in mammalian somatic tissue and in the germline. The roles of noncoding RNAs are interrogated genome- and transcriptome-wide by employing a combination of next generation sequencing technologies and high-throughput genetic screening approaches, developing computational methods, along with applying experimental techniques.. The group uses an integrative and collaborative approach, and works closely with experimental and computational groups at the Karolinska Institute (KI), Science for Life Laboratory (SciLifeLab), and other local and international research groups.
Tasks / purpose
The successful applicant will develop and integrate novel transcriptome- and genome-wide computational methods (based on RNA- and ChIP-sequencing data) to study genomic sequence and epigenetic signatures (enhancer, promoters and polymerase activity) as well as the regulatory mechanisms of noncoding RNAs in mammalian cell lines. The work implies original research in computational biology, designing computational methods and implementing existing analytical pipelines to infer underlying molecular mechanisms. The post holder will take a strong lead in the project design and management, data generation and interpretation, and collaborate with other team members. The ideal candidate is expected to report the scientific results by writing scientific papers, attending scientific meetings, and effectively communicate with peers. The ability to work in a highly interdisciplinary and international environment, and to engage in continuous professional development is a must.
- Original research contributions as part of the group’s core program
- Project leadership
- Establishment of research methodologies
- Analysis, management, communication and publishing of research findings and software tools
- Active participations in academic research activities (group meetings, journal clubs, seminar participation, continuous training in form of workshops, supervision of junior staff)
- Presenting at national and international scientific meetings
Skills and meriting
A strong background in genomics, computational biology, and/or statistics as well as experience in high-throughput genomic data analysis, extensive scripting and programming knowledge (Python, R/Bioconductor), data integration and regulatory network analysis, and data visualization is required. Candidates wishing to combine computational and experimental approaches
should be proficient in methodologies related to functional genomics (e.g ChIP-seq, RNA-seq, ATAC-seq, GRO-seq, HiC or equivalent).Prior knowledge in eukaryotic RNA biology, gene regulation, and transcriptome-wide studies as well as retrieving and analysis of genome-wide data from public domains is an asset.
The ideal candidate should be collaborative, scientifically adventurous, curiosity-driven, and should bring independent and original ideas into the project. Any previous records of independent research as well as productive interactions within a multi-disciplinary team environment (e.g. first- and/or co-author publications in high profile journals) are advantageous. All applicants should be eager to learn new concepts and acquire new skills, have good communication skills, be proficient in spoken and written English, and work effectively with other group members and researchers from other fields.
Practical information of the position
By Fellow group leader: Claudia Kutter
Email address: Claudia.email@example.com
Length of employment: flexible, min. 2 years with potential for prolongation
Other information: For more information on the work of the laboratory, please visit http://ki.se/en/mtc/claudia-kutter-group or https://www.scilifelab.se/researchers/claudia-kutter/
How to apply
The application is to be submitted on the MyNetwork recruitment system: https://ki.mynetworkglobal.com/en/what:job/jobID:229154