Job description

Pattern Ag is an agricultural technology company leveraging advances in genomics, data science, and microbiology to help farmers improve the productivity, profitability, and sustainability of their land. By applying genomic analysis to farm soil, we unlock a wide range of predictive insights that help farmers improve their soil health and optimize their spend on seed, crop protection, and fertility inputs. Combining these insights with the latest in digital sensing, data science, and machine learning, we are ushering in the era of predictive agriculture, powering on-farm decision making for millions of acres, and billions in crop spend.

We are seeking an experienced computational biologist to join our bioinformatics team within Data Science. The bioinformatics team develops models, pipelines, and pattern analyses for soil genome data. We are looking for someone with strong code skills and a deep passion for comparative genomics to work cross disciplinarily with our R&D teams. If you are excited to be a part of developing tools and insights to increase the sustainability of modern agriculture then we look forward to meeting!

Responsibilities

• Discover novel genes, pathways and regulatory motifs pertinent to discovery programs
• Recommend wet lab experiments to prove or disprove hypothesis generated by computational discovery
• Expand the capabilities of current gene annotation pipelines and in-house gene uniqueness algorithms
• Identify homologous genes and generate unique HMMs that are relevant to discovery programs
• Collaborate cross-functionally with a variety of teams, working closely with scientists, engineers, and product managers to inform and prioritize R&D genomic enhancements

Required skills and/or experience

• PhD or MS in a relevant scientific discipline with a minimum 1 year industry experience preferred in comparative and pan-'omics
• Strong programming skills in Python as well as comfort in command line tools
• Broad knowledge of NGS analysis tools and methods, including classification tools and databases, with the ability to rapidly and judiciously evaluate new tools
• Experience with virtual environments
• Experience with HMMer and HMM based gene detection and ab initio gene detection
• Experience with gene annotation in eukaryotic & prokaryotic data
• Sufficient experience in wet lab genomics to have an understanding of data quality, processes, and the linkages of these to genomic outcomes
• Strong written and oral communication skills

Nice to have skills

• Experience working with AWS or GCP or HPC or Jetstream environments
• Experience with relational databases and SQL
• ML techniques as applied in computational genomics such as hierarchical clustering, bayesian matching algorithms, SVMs, HMMs, and dimensional reduction

Compensation

• $110,000/yr - $135,000/yr

Thank you for considering Pattern Ag. We look forward to reviewing your application!

Job Type: Full-time

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