The Earlham Institute has been awarded funding by the Gordon and Betty Moore Foundation to develop Protist Omics at Scale, a three-year international methods-development programme run in partnership with the Scottish Association for Marine Science, home of the Culture Collection of Algae and Protozoa, and the Bigelow Laboratory for Ocean Sciences.

We are looking for a computational biologist to lead the computational core of the project: quality control, assembly, decontamination and co-biont separation, and structural and functional annotation across all three aims. Where existing tools fail, the postholder will diagnose why and develop what replaces them.

The post is based at the Earlham Institute on the Norwich Research Park.

Background:

Protists represent the vast majority of eukaryotic diversity but remain significantly under-represented in reference genome databases. Their genomes are often large, repetitive and genetically complex, and are frequently derived from mixed, low-biomass or uncultured samples, making them difficult to assemble and annotate using standard genomic approaches.

This project aims to address these challenges by systematically identifying and overcoming key bottlenecks in genome and transcriptome assembly across three areas:
1. Cultured protists with sufficient biomass.
2. Protists that can only be grown at low concentrations.
3. Single-cell genomes and transcriptomes from uncultured environmental protists.

Based within the Earlham Institute's Director's Group, the project combines expertise in long-read sequencing, single-cell genomics, spatial biology and computational biology. It brings together leading facilities at the Earlham Institute, including the Technical Genomics Group and the Single-Cell and Spatial Analysis Platform, as well as external collaborators at CCAP/SAMS, home to one of the world's largest protist culture collections, and the Bigelow Laboratory Single Cell Genomics Center, a world-leading centre for environmental microorganism genomics.

The overall objective is to develop and apply innovative methods that enable the generation of high-quality genomic and transcriptomic resources for previously inaccessible and poorly characterised eukaryotic organisms.

The role:

This is a postdoctoral computational biology/bioinformatics role focused on developing and applying novel methods for long-read and single-cell genome and transcriptome assembly across a diverse range of protist species.

The postholder will:

• Develop expertise in advanced genome and transcriptome assembly approaches.
• Work on complex long-read and single-cell sequencing datasets.
• Contribute to the development of new computational methods rather than routine analysis.
• Develop research software engineering skills, including workflow development, packaging and containerisation.
• Create and maintain reproducible bioinformatics workflows using platforms such as Galaxy and WorkflowHub.
• Collaborate closely with internal and external partners across the consortium.
• Lead or contribute significantly to computational project outputs.
• Publish research findings and present at national and international conferences.
• Participate in workshops, hackathons and community training activities.
• Support the supervision and development of students where appropriate.
The role offers extensive opportunities for career development, networking and collaboration within an internationally recognised genomics research environment.

The ideal candidate:

The post holder will have, or be close to completing, a PhD in bioinformatics, computational biology, genomics, evolutionary biology or a closely related discipline.

They will have practical experience of analysing large-scale next-generation sequencing datasets and de novo genome assembly using long-read sequencing data (PacBio HiFi and/or Oxford Nanopore), together with proficiency in at least one bioinformatics programming language and experience working in a Linux/HPC environment.

The successful candidate will have experience of genome or transcriptome analysis, an ability to critically evaluate computational methods, and a track record of contributing to research outputs, including peer-reviewed publications.

Experience of workflow development and reproducible research practices, including version control and workflow management systems, would be advantageous, as would knowledge of single-cell genomics, protist or microbial eukaryote biology, and software containerisation technologies.