A postdoc position is available in my group, to develop machine learning methods for inferring causal gene networks from genome, epigenome and transcriptome sequencing data. For more information and application instructions, see here.
Four PhD positions in computer science are available at the Department of Informatics. These positions can be held in any of the department’s research areas (algorithms, bioinformatics, machine learning, optimization, programming theory, security, and visualization). Applicants with an interest in computational biology and machine learning are welcome to contact me prior to submitting their application.
For more details and application instructions, see here.
A PhD project in the MRC funded Precision Medicine Doctoral Training Programme is available. The project will study cortisol-responsive gene networks in cardiovascular disease and is a collaboration with Filippo Menolascina (Synthetic Biology) and Brian Walker (Cardiovascular Science). Project details and application guidelines are here. Application deadline 9 January 2017!
The Systems Genomics group at the Roslin Institute at the University of Edinburgh headed by Dr Tom Michoel develops and applies analytical methods and software to model the complex variations of traits and diseases between individuals using large-scale multi-omics data. We are currently seeking two highly motivated postdoctoral Research Fellows to join our team.
The first position is funded by Roslin Institute Strategic Grant Funding from the BBSRC and will focus on the development and implementation of novel analytical methods for reconstructing causal gene networks from multi-omics data. Specific areas of interest include the modelling of cross-sectional transcriptome time series, the joint modelling of cis- and trans-eQTL associations in regulatory module networks, and the integrative modelling of transcriptome and metabolome data. Newly developed methods will be validated on published and unpublished data from experimental collaborators. This position requires a very strong background in statistical modelling and computer programming. A PhD degree in physics, informatics, mathematics, statistics or engineering is essential, and previous experience in working with large-scale omics data is a plus. The position is available immediately and is initially funded until 2019, with possibility of extension (subject to renewal of the Roslin Institute Strategic Grant Funding).
The second position is funded by the NIH and is part of a collaboration with the Icahn Institute for Genomics and Multiscale Biology at the Icahn School of Medicine at Mount Sinai in New York, aimed at discovering novel diagnostics and therapies of molecular subcategories of coronary artery disease (CAD) patients, centred around the analysis of a unique dataset of genotype and RNA-sequencing data from seven disease-relevant tissues of 600 CAD patients. This position will focus in particular on reconstructing causal gene networks for specific phenotypic subcategories of patients, and validating these networks in the context of existing GWAS, regulatory genomics (e.g. ENCODE and RoadMap Epigenomics) and other relevant datasets. This position requires previous experience in working with large-scale omics data and a strong computer programming background. A PhD degree in a computational science (e.g. bioinformatics, statistical genetics, physics, informatics, mathematics, statistics or engineering) is desired. Candidates with a PhD degree in the life sciences are welcome to apply, provided they can demonstrate a strong proficiency in statistics and computer programming. The position is available immediately and is funded for two years.
Applications or informal queries regarding the positions should be addressed to Dr Tom Michoel – Tom.Michoel@roslin.ed.ac.uk.
We are seeking a highly motivated Research Fellow to work on a project funded by the Tools and Resources Development Fund of the Biotechnology and Biological Sciences Research Council. The project is a collaboration with the research group of Dr Albert Tenesa and focuses on the development of novel computational methods for reconstructing causal gene networks from large-scale omics data to understand how the genotype determines the phenotype. The successful applicant will have the opportunity to work in a highly interdisciplinary and stimulating environment with access to unique datasets of genotype, RNA-sequencing and phenotype information across hundreds of individuals. The ideal candidate will have a PhD degree (or equivalent experience) in a computational science (e.g. informatics, statistics, bioinformatics, statistical genetics, engineering, applied mathematics, physics) with expertise in developing algorithms for analysing large-scale omics data. For any queries regarding the post, please contact Dr Tom Michoel. Deadline for applications
31 March 2015 extended to 13 May 2015.