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You must be comfortable working in a multidisciplinary environment, have excellent communication skills, and be comfortable working independently. The role calls for a detail-oriented and highly motivated individual with experience in python programming, nextflow workflows, and github and the ability to deliver to time and target. Eligible candidates will have a Masters or PhD in Bioinformatics or Computational Biology, with proven programming experience in Python and Nextflow. An ability to work independently and within strict timelines is essential.
- Devising algorithms and writing software to convert raw data (typically genomic sequencing data) into diagnoses
- Performing ad-hoc bioinformatic analyses as required for the GIU and collaborators
- Presenting results at internal and external meetings and conferences
- Keeping up to date with the latest research literature towards finding or evaluating new projects
- Helping to write scientific publications
The Genomics Innovation Unit (GIU) at Guy's and St. Thomas' NHS Trust is looking to grow its team strategically, adding a talented computational biologist to help us expand our capabilities and take on more projects simultaneously, while remaining nimble, dynamic, and effective. The primary project for this role will involve developing algorithms and implementing pipelines to analyse genomic and transcriptomic datasets towards the rapid detection of different types of cancer.
In addition, the GIU develops novel genomic diagnostic tests, and in the process innovates new experimental approaches. Sinch the experimental workflows are customised for each project, the computational workflows also have to be tailored to suit each application. GIU projects typically involve genomic sequencing of patient samples, including but not limited to Oxford Nanopore and Illumina sequencing. This part of the role will involve developing algorithms and writing software to convert raw sequencing data into diagnoses, using in-house code and off-the shelf components. Another important aspect of this job will be providing bioinformatic support for our many collaborations with academics from King's College London, and several NHS Trusts. Finally, the GIU is making strides into using machine learning for genomic applications, for which we have access to in-house and HPC GPUs. There is room within this role to pursue cutting-edge projects applying deep learning to genomic and proteomic data.
The GIU develops novel genomic diagnostic tests, and in the process innovates new experimental approaches. Since the experimental workflows are customised for each project, the computational workflows also have to be tailored to suit each application. Experimentally, GIU projects typically involve genomic sequencing of patient samples, including but not limited to Oxford Nanopore and Illumina sequencing. This part of the role will primarily involve developing algorithms and writing software to convert raw sequencing data into diagnoses, using in-house code and off-the shelf components. Another important aspect of this job will be providing bioinformatic support for our many collaborations with academics from King's College London, and several NHS Trusts. Finally, the GIU is making strides into using machine learning for genomic applications, for which we have access to in-house and HPC GPUs. There is room within this role to pursue cutting-edge projects applying deep learning to genomic and proteomic data.
You must be comfortable working in a multidisciplinary environment, have excellent communication skills, and be comfortable working independently. The role calls for a detail-oriented and highly motivated individual with experience in python programming, nextflow workflows, and github and the ability to deliver to time and target. Eligible candidates will have a Masters or PhD in Bioinformatics or Computational Biology, with proven programming experience in Python and Nextflow. An ability to work independently and within strict timelines is essential.
- Devising algorithms and writing software to convert raw data (typically genomic sequencing data) into diagnoses
- Performing ad-hoc bioinformatic analyses as required for the GIU and collaborators
- Presenting results at internal and external meetings and conferences
- Keeping up to date with the latest research literature towards finding or evaluating new projects
- Helping to write scientific publications
The Genomics Innovation Unit (GIU) at Guy's and St. Thomas' NHS Trust is looking to grow its team strategically, adding a talented computational biologist to help us expand our capabilities and take on more projects simultaneously, while remaining nimble, dynamic, and effective. The primary project for this role will involve developing algorithms and implementing pipelines to analyse genomic and transcriptomic datasets towards the rapid detection of different types of cancer.
In addition, the GIU develops novel genomic diagnostic tests, and in the process innovates new experimental approaches. Sinch the experimental workflows are customised for each project, the computational workflows also have to be tailored to suit each application. GIU projects typically involve genomic sequencing of patient samples, including but not limited to Oxford Nanopore and Illumina sequencing. This part of the role will involve developing algorithms and writing software to convert raw sequencing data into diagnoses, using in-house code and off-the shelf components. Another important aspect of this job will be providing bioinformatic support for our many collaborations with academics from King's College London, and several NHS Trusts. Finally, the GIU is making strides into using machine learning for genomic applications, for which we have access to in-house and HPC GPUs. There is room within this role to pursue cutting-edge projects applying deep learning to genomic and proteomic data.
The GIU develops novel genomic diagnostic tests, and in the process innovates new experimental approaches. Since the experimental workflows are customised for each project, the computational workflows also have to be tailored to suit each application. Experimentally, GIU projects typically involve genomic sequencing of patient samples, including but not limited to Oxford Nanopore and Illumina sequencing. This part of the role will primarily involve developing algorithms and writing software to convert raw sequencing data into diagnoses, using in-house code and off-the shelf components. Another important aspect of this job will be providing bioinformatic support for our many collaborations with academics from King's College London, and several NHS Trusts. Finally, the GIU is making strides into using machine learning for genomic applications, for which we have access to in-house and HPC GPUs. There is room within this role to pursue cutting-edge projects applying deep learning to genomic and proteomic data.
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