Job ID: SW11171
Job date: 2017-01-18
End Date:
Company : University of Cambridge Country : Role : Research Scientist
Job date: 2017-01-18
End Date:
Company : University of Cambridge Country : Role : Research Scientist
Job Description:
The Markowetz lab in the Cancer Research UK Cambridge Institute at the University of Cambridge is looking for an outstanding candidate to work on inferring patterns of tumour evolution from genomics data. We will analyse two types of data: (1) large cohorts of single-sample bulk sequenced tumours from the TCGA and ICGC pan-cancer projects as well as from other sources, and (2) genomes of single cells from individual tumours. We plan to adapt methods from population genetics and phylogenetics to the cancer setting. Key problems will be to compare mutation rates and selection hotspots between the genomes of cancer clones. This position is ideal for somebody trained in evolutionary biology in model systems to make the transition to biomedical applications in cancer. The successful applicant will have a PhD in a quantitative field like mathematics, statistics, physics, engineering, bioinformatics, or computer science. A background in evolutionary biology, molecular evolution or population genetics is highly desired. The applicant should have a good biological background and excellent computing skills. The atmosphere at CI is very collaborative and interactive; good communication skills are key.
Additional Info:
References: -Beerenwinkel et al (2014) Cancer evolution: mathematical models and computational inference, Systematic Biology. -Ross and Markowetz (2016), OncoNEM: Inferring tumour evolution from single-cell sequencing data, Genome Biology, 17:69 -Schwarz et al (2015), Spatial and temporal heterogeneity in high-grade serous ovarian cancer: a phylogenetic reconstruction, PLoS Med, 12(2) -Yuan et al (2015), BitPhylogeny: A probabilistic framework for reconstructing intra-tumor phylogenies, Genome Biol, 16:36 Fixed-term: The funds for this post are available for 2 years in the first instance. Once an offer of employment has been accepted, the successful candidate will be required to undergo a basic disclosure (criminal records check) check and a security check. To apply online for this vacancy and to view further information about the role, please visit: http://www.jobs.cam.ac.uk/job/12614. This will take you to the role on the University’s Job Opportunities pages. There you will need to click on the 'Apply online' button and register an account with the University's Web Recruitment System (if you have not already) and log in before completing the online application form. The closing date for applications is 19th February 2017. With the interview date TBC. Please include details of your referees, including email address and phone number, one of which must be your most recent line manager. Please ensure that you upload a covering letter and CV in the Upload section of the online application. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application. Please quote reference SW11171 on your application and in any correspondence about this vacancy. The University values diversity and is committed to equality of opportunity. The University has a responsibility to ensure that all employees are eligible to live and work in the U.K.[Click Here to Access the Original Job Post]
The Markowetz lab in the Cancer Research UK Cambridge Institute at the University of Cambridge is looking for an outstanding candidate to work on inferring patterns of tumour evolution from genomics data. We will analyse two types of data: (1) large cohorts of single-sample bulk sequenced tumours from the TCGA and ICGC pan-cancer projects as well as from other sources, and (2) genomes of single cells from individual tumours. We plan to adapt methods from population genetics and phylogenetics to the cancer setting. Key problems will be to compare mutation rates and selection hotspots between the genomes of cancer clones. This position is ideal for somebody trained in evolutionary biology in model systems to make the transition to biomedical applications in cancer. The successful applicant will have a PhD in a quantitative field like mathematics, statistics, physics, engineering, bioinformatics, or computer science. A background in evolutionary biology, molecular evolution or population genetics is highly desired. The applicant should have a good biological background and excellent computing skills. The atmosphere at CI is very collaborative and interactive; good communication skills are key.
Requeriments :
Skills :
Areas :
Additional Info:
References: -Beerenwinkel et al (2014) Cancer evolution: mathematical models and computational inference, Systematic Biology. -Ross and Markowetz (2016), OncoNEM: Inferring tumour evolution from single-cell sequencing data, Genome Biology, 17:69 -Schwarz et al (2015), Spatial and temporal heterogeneity in high-grade serous ovarian cancer: a phylogenetic reconstruction, PLoS Med, 12(2) -Yuan et al (2015), BitPhylogeny: A probabilistic framework for reconstructing intra-tumor phylogenies, Genome Biol, 16:36 Fixed-term: The funds for this post are available for 2 years in the first instance. Once an offer of employment has been accepted, the successful candidate will be required to undergo a basic disclosure (criminal records check) check and a security check. To apply online for this vacancy and to view further information about the role, please visit: http://www.jobs.cam.ac.uk/job/12614. This will take you to the role on the University’s Job Opportunities pages. There you will need to click on the 'Apply online' button and register an account with the University's Web Recruitment System (if you have not already) and log in before completing the online application form. The closing date for applications is 19th February 2017. With the interview date TBC. Please include details of your referees, including email address and phone number, one of which must be your most recent line manager. Please ensure that you upload a covering letter and CV in the Upload section of the online application. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application. Please quote reference SW11171 on your application and in any correspondence about this vacancy. The University values diversity and is committed to equality of opportunity. The University has a responsibility to ensure that all employees are eligible to live and work in the U.K.[Click Here to Access the Original Job Post]