Senior Scientist, AMR Genomics - Pathogen

Senior Scientist, AMR Genomics - Pathogen

EIT - Ellison Institute of Technology

Oxford, United Kingdom

Your Role

We are looking for a Senior Scientist with expertise in AMR genomics to join the Pathogen Program. This is a predominantly desk-based role working collaboratively across teams within the Pathogen Program to provide expert input on a range of AMR related tasks and topics. You will curate expert rules for interpretation of AMR genotypic data, provide domain-specific analysis and support for genome sequence and AST data generated by the laboratory, provide expert advice for AST testing and investigate putative novel mechanisms of resistance.

This is an excellent opportunity for an enthusiastic individual with a passion for AMR and strong domain-specific knowledge to contribute to an ambitious program of work aiming to revolutionise pathogen diagnostics.

Key Responsibilities

• Provide expert knowledge and input into research and operational activities involving antimicrobials and AMR;
• Develop expert rules for prediction of antimicrobial phenotype from genotypic information;
• Curate catalogues of antimicrobial resistance loci, such as AMRFinderPlus output;
• Contribute to design and quality assurance of antimicrobial susceptibility testing;
• Review paired antimicrobial susceptibility and whole genome sequence data to identify possible anomalies or areas for further investigation;
• Review existing MIC data and identify priorities for further testing or re-testing;
• Interpret and curate data on plasmids and mobile genetic elements from genomic and metagenomic datasets;
• Collaborate with colleagues developing Machine Learning models for AMR prediction from genotype;
• Contribute to research to identify and investigate novel antimicrobial resistance mechanisms identified by Machine Learning models;
• Collaborate with laboratory scientists to produce and evaluate datasets for identification of AMR genes and prediction of antimicrobial susceptibility from metagenomic data;
• Liaise with key internal and external stakeholders involved in EIT’s AMR-related activities;
• Opportunity to conduct laboratory research to generate datasets for identification of AMR genes and prediction of antimicrobial susceptibility from metagenomic data;
• Opportunity to contribute to laboratory research investigating putative novel antimicrobial resistance loci;
• Keep up with the latest literature relevant to the field;
• Keep excellent records of work performed;
• Analyse and summarise data, and present data and results at internal or external meetings as required.

Requirements

Essential Knowledge, Skills, and Experience:

• A PhD degree in a relevant scientific discipline (e.g. microbiology, molecular microbiology clinical biology biochemistry);
• over 2 years of post-doctoral research experience;
• Significant research experience in antimicrobial resistance;
• Significant experience working with and interpreting genomic data from bacteria;
• Strong data analysis skills and familiarity with data analysis packages such as R;
• Good communication skills;
• Excellent record-keeping and attention to detail;
• Strong IT skills and experience using spreadsheets, word processing and presentation software.

Desirable Knowledge, Skills, and Experience:

• Research experience in AMR genomics;
• Research experience with plasmids or other mobile genetic elements;
• Basic bioinformatic skills;
• Microbiology and/or molecular biology laboratory skills;
• Familiarity with metagenomic workflows and data;
• Experience working with nanopore sequencing;
• Previous experience of using Confluence, Jira, Lucidchart or other similar reporting and project management tools.

Key Attributes:

• Enthusiastic and proactive individual with a “can-do” attitude;
• Ability to work effectively in a high-growth, fast-paced, dynamic environment;
• Ability to work independently and prioritise tasks;
• Collaborative team-player, able to work well within multi-disciplinary teams;
• Excellent oral and written communication skills, interpersonal skills, and the ability to work with a wide range of people from diverse backgrounds;
• Ability to effectively communicate across scientific domains;
• Good problem-solving skills;
• Highly organised, with excellent time management and prioritisation abilities.