BFF-AFIRMS Data Coordinator

University of Alberta Careers; Edmonton; On-site; CAD 70,000 - 96,000; Full time

Job summary

BFF-AFIRMS at North Campus, Edmonton, is seeking a Data Coordinator for a 2-year term to help build data infrastructure and governance for a cross-institution forest genomics initiative.

You will curate genomic and phenotypic data, design and test a relational database, and optimize data flows to support tree-improvement decision making while collaborating with researchers and partners.

Qualifications

• Understanding of data collection and management in genetics/genomics and scientific computing.

Responsibilities

• Support development of data/computing infrastructure and decision-making workflow.
• Improve data flow across disciplines for tree-improvement decision-making, and facilitate communication among stakeholders.

Skills

Genomics data

Relational DBs

Data governance

Cross-functional collab

SQL

Tools

SQL

Job description

This position has a term length of 2 years with the possibility of extension.

Location - This role is in-person. Work primarily takes place at North Campus, Edmonton.

BFF-AFIRMS, (Best Future Forest: Advanced Forest Genomics and Integrative Resource Management System), is a transformative initiative aimed at digitalizing forest resource management and tree improvement in Alberta (AB), Canada (CA). This is a joint effort across the Government of Alberta (GoA), forest industry partners of Tree Improvement of Alberta, University of Alberta (UofA, CA), and Oklahoma State University (USA). The initiative seeks to integrate high-throughput genotyping, predictive analytics, and decision-making science to ensure responsible stewardship of forest genetic resources in the face of climate challenges, and the growing demand for sustainable forest ecosystems and products.

Working with the BFF-AFIRMS team, the Data Coordinator will join our interdisciplinary team and support the development of BFF-AFIRMS data/computing infrastructure, decision-making workflow, and user experience. The ideal candidate will play a critical role in data curation and governance, collaborating with the database scientist to design, test, and maintain a relational database that manages large volumes of genomic, phenotypic, climate and site information, and tree improvement data. As the primary interface between scientific computing and our diverse range of end-users and stakeholders, the candidate will also be responsible for optimizing data flow across various disciplines for tree improvement decision-making, and facilitating seamless communication within the project.

The candidate will have an understanding of data collection and management in genetics, genomics, scientific computing, as well as familiarity with tree improvement programs, breeding data, and forest genetic resources. A passion for working in a highly multi-disciplinary and collaborative environment to support forest genomics and tree improvement programs is essential.