Senior Computational Microbiologist - 100%

At CellX Biosolutions AG, an innovative ETH spin-off, we develop microbial solutions to degrade persistent environmental pollutants such as PFAS and pesticides. Our mission is to bring the world's first commercial bacterial solution for PFAS remediation from the lab into real-world industrial application.Role OverviewWe are looking for a Senior Computational Microbiologist to build and lead our in-house computational and molecular microbiology capability from the ground up. You will establish a mechanistic and metabolic understanding of how our bacterial strains and communities degrade PFAS and other persistent chemicals. You will translate this understanding into a computational pipeline that predicts strain performance and guides the rational design of synthetic microbial communities for specific use-cases.This role bridges computation and experiment. You will work hands-on with sequencing data (Illumina, Oxford Nanopore & PacBio) as well as other omics and analytical data streams. You will also design the experiments that validate computational predictions in our strains. You will supervise a Laboratory Technician who supports wet-lab and sequencing workflows. This is a senior, high-impact, 100% onsite role with the freedom and responsibility to shape CellX's data-inferred product development as we move from the lab to the field.Main ResponsibilitiesTeam leadership & supervision- Supervise and mentor our Laboratory Technician involved in the project, coordinating wet-lab, cultivation, and sequencing workflows (Illumina, Oxford Nanopore, PacBio) to ensure high-quality data for downstream analysis- Set priorities and quality standards for sample preparation, sequencing, and data handover between wet lab and bioinformaticsBioinformatics pipeline development-Design, build, and maintain an in-house bioinformatics pipeline covering genome assembly, annotation, and comparative genomics from short-read and long-read sequencing data-Evaluate and integrate the best available tools and methods, including AI/ML approaches, for genome mining, functional annotation, and strain characterization-Ensure the pipeline is reproducible, scalable, and not limited to current technologies, so it can incorporate new sequencing and omics data types as they become relevantMetabolic understanding & PFAS degradation-Establish a metabolic-level understanding of how our bacterial strains degrade PFAS, identifying the genes, enzymes, and pathways involved-Build and apply genome-scale...

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