3 of 3 Remote/Hybrid Genomics Jobs in Oxford

that are accurate and robust enough to be integrated into our infectious disease diagnostic product. You will report to the Lead Scientist in Computational Genomics, and you will work closely with bioinformaticians, data scientists, microbiologists, and software engineers to deliver clinically relevant innovation in the microbial genomics space. Key Responsibilities … computational algorithms in areas such as taxonomic classification and antimicrobial resistance Develop ML/AI techniques to address real-world problems in the pathogen genomics space, in collaboration with scientists across EIT Validate and benchmark methods using public and internal datasetsWork with bioinformaticians and software engineers to implement methods ...

Your new company You'll be joining an innovative research team developing next-generation technologies at the intersection of genomics, artificial intelligence, and healthcare. You'll be part of a multidisciplinary department of computational scientists, bioinformaticians, engineers, and researchers applying advanced analytics to large-scale biological datasets and real-world … site (preferably 3 days/week but potentially flexible for the right candidate). Key responsibilities include: Designing and developing novel algorithms for genomics, sequencing, and large-scale biological data analysis Building and evaluating machine learning models to address complex scientific and translational research questions Validating and benchmarking new computational ...

Your new company You'll be joining an innovative research team developing next-generation technologies at the intersection of genomics, artificial intelligence, and healthcare. You'll be part of a multidisciplinary department of computational scientists, bioinformaticians, engineers, and researchers applying advanced analytics to large-scale biological datasets and real-world … site (preferably 3 days/week but potentially flexible for the right candidate). Key responsibilities include: Designing and developing novel algorithms for genomics, sequencing, and large-scale biological data analysis Building and evaluating machine learning models to address complex scientific and translational research questions Validating and benchmarking new computational ...