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Job: Post-doc or Senior-Post doc Bioinformatician
Place: University of Cambridge UK
Duration: Until March 2017
Further information: http://www.jobs.cam.ac.uk/job/2235
This is a NIHR funded post in the Department of Obstetrics & Gynaecology at the University of Cambridge, available until 31 March 2017 in the first instance. It will involve analysis of sequence data from a number of sources, but focusing on samples of the placenta from pregnancies complicated by pre-eclampsia and/or fetal growth restriction, compared with matched controls. Analyses will include the placental genome, the methylome (using whole genome bisulphite sequencing) and RNA profile (both coding and non-coding). Samples have already been collected and archived through the Women’s Health theme of the NIHR Cambridge Comprehensive Biomedical Research Centre: see http://www.biomedcentral.com/1471-2393/8/51 for study design. Samples are available from a cohort of ~4,500 women. Wetlab studies are currently being conducted by two experienced post-doctoral research associates and sequencing will be performed using a HiSeq2500 run by the on-site Genomic core facility.
The overarching aim of the project is to use sequence-based analyses of the placenta from normal and complicated pregnancy to identify candidate biomarkers for major complications of pregnancy. We have ~17,000 stored serum and plasma samples from the same cohort, obtained serially through the pregnancy, to test and validate any potential biomarkers identified.
Applicants should have (or close to obtaining) a relevant MSc or PhD in the fields of bioinformatics, scientific data analysis, machine learning, or related fields. Expertise in the areas of scientific programming (e.g. in Python, Perl, C, Java, etc.), handling biological information in databases, data mining and analysis packages (such as Bioconductor) are essential for the post, as is a general understanding of biological information. Previous experience in the analysis of high throughput biological data would be highly advantageous, as is previous demonstrated experience in leading projects and working in interdisciplinary teams.
The candidate would join two other full time computational posts (a Senior Research Associate in Biostatistics and a Research Associate in Bioinformatics). We have close collaborative links with the nearby MRC Biostatistics Unit and the CRUK Cambridge Institute. We also have a related project running in collaboration with the Sanger Institute, the staff supported on this MRC funded grant (wet-lab post doc and a bioinformatician) will also interact with the person appointed to this post.
Place: University of Cambridge UK
Duration: Until March 2017
Further information: http://www.jobs.cam.ac.uk/job/2235
This is a NIHR funded post in the Department of Obstetrics & Gynaecology at the University of Cambridge, available until 31 March 2017 in the first instance. It will involve analysis of sequence data from a number of sources, but focusing on samples of the placenta from pregnancies complicated by pre-eclampsia and/or fetal growth restriction, compared with matched controls. Analyses will include the placental genome, the methylome (using whole genome bisulphite sequencing) and RNA profile (both coding and non-coding). Samples have already been collected and archived through the Women’s Health theme of the NIHR Cambridge Comprehensive Biomedical Research Centre: see http://www.biomedcentral.com/1471-2393/8/51 for study design. Samples are available from a cohort of ~4,500 women. Wetlab studies are currently being conducted by two experienced post-doctoral research associates and sequencing will be performed using a HiSeq2500 run by the on-site Genomic core facility.
The overarching aim of the project is to use sequence-based analyses of the placenta from normal and complicated pregnancy to identify candidate biomarkers for major complications of pregnancy. We have ~17,000 stored serum and plasma samples from the same cohort, obtained serially through the pregnancy, to test and validate any potential biomarkers identified.
Applicants should have (or close to obtaining) a relevant MSc or PhD in the fields of bioinformatics, scientific data analysis, machine learning, or related fields. Expertise in the areas of scientific programming (e.g. in Python, Perl, C, Java, etc.), handling biological information in databases, data mining and analysis packages (such as Bioconductor) are essential for the post, as is a general understanding of biological information. Previous experience in the analysis of high throughput biological data would be highly advantageous, as is previous demonstrated experience in leading projects and working in interdisciplinary teams.
The candidate would join two other full time computational posts (a Senior Research Associate in Biostatistics and a Research Associate in Bioinformatics). We have close collaborative links with the nearby MRC Biostatistics Unit and the CRUK Cambridge Institute. We also have a related project running in collaboration with the Sanger Institute, the staff supported on this MRC funded grant (wet-lab post doc and a bioinformatician) will also interact with the person appointed to this post.