Job Skills: Programming in R
The primary job responsibility of the selected candidate will be the management of the main analysis pipeline used at TGen to automate the analysis of next-generation sequencing data. This job will involve frequent interactions with project leaders around the institute to develop project specific processes and to ensure projects are analyzed in timely manner. The successful candidate can expect to be exposed to a diverse array of diseases and will be a key member of our analytical team working to improve the health and outcomes for our patients. [More]
The Bioinformatician will provide bioinformatics expertise and support for metagenomic sequence analysis, including benchmarking and evaluation of different free and open source (F/OSS) and Commercial off the Shelf (CotS) software products for pathogen genomics, metagenomics and metatranscriptomics. [More]
We are seeking an MS biostatistician with biomedical research background to join the Cancer Biostatistics Core of the Huntsman Cancer Institute. The person filling this position will write detailed analysis plans, carry out statistical analyses, and interpret analysis results, and must be able work effectively in a multidisciplinary group with regard to study design, statistical programming, analysis of data, and learning new statistical methods. The successful candidate will perform analyses of methylation, gene expression and metabolomics data, and will perform analyses of genetic epidemiology data, cancer survival and prognosis. [More]
Bioinformatics scientists provide bioinformatics and statistical analysis support for biomarker discovery, IVD product development and CMI tumor molecular profiling service. [More]
The Gerstung group is looking for a highly talented postdoctoral researcher to contribute to their research in computational cancer biology. Research in the group includes large-scale international projects such as the ICGC PanProstate consortium utilising cloud computing to enhance our understanding of prostate cancer. [More]
We are looking for an enthusiastic and talented postdoctoral researcher to join the lab of Associate Professor Olof Emanuelsson, affiliated with the School of Biotechnology at KTH Royal Institute of Technology in Stockholm. The work will consist of bioinformatics method development for massively parallel sequencing data, with particular focus on RNA-seq, including allele-specific expression (ASE) and transcriptome assembly. [More]
The incumbent of this position will be responsible for the management, processing, and analysis of deep sequencing data from a variety of collaborative projects. The successful candidate will take part in streamlining existing analysis pipeline and developing custom computational strategies for deep sequencing data. This candidate will interact regularly with scientists from different backgrounds including experimental biologists in the Lab. The successful candidate will be self-motivated, and enjoy working in a highly collaborative research environment. [More]
We are seeking a highly motivated Scientist or Sr. Scientist to join our efforts at Fulcrum. This individual will focus primarily on next generation sequencing data in conjunction with human or model organism phenotypic data as it relates to our therapeutic programs. [More]
The "Genotype & Environment to Phenotype (GE2P)" theme in P2IRC is seeking a post-doctoral fellow to work as part of an interdisciplinary and collaborative team consisting of seven faculty and their graduate students. The team is led by Drs. Anthony Kusalik and Michael Horsch.he successful candidate will work as part of the GE2P team to identify and predict connections between phenotypic features and genotype and environmental factors in crop species. Activities will be directly supervised by Dr. Kusalik and Dr. Matthew Links. The research will take advantage of the local computer and software resources provided by other Computer Science teams in P2IRC, as well as HPC facilities at the U. of Saskatchewan and at Compute Canada. [More]
The position primarily involves the management and integration of complex biomedical data for research purposes within various projects and consortia. This will include the setup and maintenance of knowledge and data management servers (e.g. openBIS, Wikis, tranSmart) as well as the implementation of ETL data pipelines. Further tasks will include statistical analyses and the integration of high-troughput data and clinical records as well as external data sources. [More]