Help bridge the gap between soil metabarcoding outputs and ecological insights, ensuring that UEPs are equipped to analyze, interpret, and publish their data.

Responsibilities

UEP Training & Support

• Host regular office hours (2x/month) to support UEPs in lab protocols trouble shooting, bioinformatics, ecological data analysis and interpretation.
• Provide one-on-one and group training in basic bioinformatics and ecological data analyses, with a focus on closing knowledge gaps, especially for researchers in the Global South.
• Provide support to UEPs seeking advice on molecular and sequencing components of projects.
• Develop and implement workshops on experimental design, statistics, and bioinformatics (online as well as in-person if funding allows).
• Select and support promising UEP datasets for enhanced analysis and publication opportunities. Potential for co-authorship on publications to be established with each UEP but not guaranteed.

Ecological & Molecular Analysis

• Support UEPs with complex ecological questions and conservation-focused data analysis. The amount of time for each project will be depending on demand and time availability.
• Provide feedback on experimental design, statistical approaches, and interpretation of results.
• Assist with quality control of sequencing data and routine troubleshooting as needed.
• Contribute to the development and refinement of bioinformatics pipelines and training tools.

Collaboration & Capacity Building

• Work closely with the data team (bioinformaticians, database architects, and molecular scientists) to align training support with existing infrastructure.
• Partner with UEPs globally to build analytical capacity and empower local researchers to lead ecological insights from their own datasets.
• Potentially share responsibilities with the expeditions team to provide training linked to field sampling.

Skillset

• PhD (or near completion) in molecular ecology, microbial ecology, or related field. Masters degree and extensive experience in fungal molecular ecology and data analyses considered.
• Strong ecological background with demonstrated experience in bioinformatics and data analysis specifically in fungal communities.
• Familiarity with molecular techniques (DNA extraction, preferably from soils, PCR, high-throughput DNA sequencing and metabarcoding).
• Familiarity with basic bioinformatics tools for sequencing analysis.
• Experience using R for ecological analyses.
• Experience analyzing mycorrhizal or fungal molecular data (preferred).
• Strong communication skills, with ability to translate technical concepts into accessible training.
• Commitment to capacity building and equitable knowledge-sharing, especially in under-resourced contexts.
• Demonstrated experience mentoring, training, or supporting peers, students, or collaborators.
• Excellent communication skills, with the ability to explain complex analyses to a broad audience.
• Collaborative mindset and willingness to contribute to support and operational tasks.
• Interest in applying scientific expertise to pre-existing datasets and community training, rather than pursuing independent research.

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