The Human Genomics Team/Genome in a Bottle at NIST (www.genomeinabottle.org) has several unique, genome bioinformatics/computational biology positions that we are looking to fill. We are excited to be expanding our team in two areas: (1) developing a new class of genomic benchmarks using Artificial Intelligence and Machine Learning , and (2) developing reference samples for somatic variants. Our team has unique work developing widely-used benchmarks for genome sequencing in an open, public Genome in a Bottle Consortium (https://rdcu.be/b4UMa, https://rdcu.be/bue67, https://rdcu.be/bqpDT, https://www.nature.com/articles/s41467-020-18564-9). We're recruiting a diverse team with interest and experience in genomics bioinformatics/computational biology at different levels (BS, MS, or PhD) and areas, e.g., scientists that could be postdocs or early career, software engineers, data engineers, data scientists, and analysts/technicians. Below we provide job descriptions for Genomics Scientist and Genomics Software Engineer. Our team focuses on high-impact applications of the latest sequencing technologies and bioinformatics methods to develop benchmarks, data, and accompanying tools resulting in some of the best-characterized genomes that meet benchmarking needs in the clinical and research communities.
Interested individuals can email Justin Zook at firstname.lastname@example.org.
Candidate would be responsible for development of benchmark data sets and/or benchmarking methods for NIST human genome reference materials. The NIST-led Genome in a Bottle Consortium (GIAB) uses an open science approach and shares data and analysis results without embargo through a public repository for processed sequencing data, draft benchmarks, and released data/benchmark sets. Candidate would ideally present a poster or talk at ~2-3 conferences per year to regularly engage with GIAB stakeholders and solicit feedback along with developing manuscripts as appropriate describing data/benchmark sets/benchmarking methods. The candidate will be expected to lead at least one project for developing a benchmark data set and/or benchmarking methods. The ideal candidate will have a background and passion for understanding strengths and biases of genomic measurements with an interest to focus on human whole genome sequencing. Ideal background includes formal training (MS with strong publication record or PhD) or work experience in bioinformatics, computational biology, computer science, applied math/statistics, or biology/genetics with appropriate command-line and programming knowledge.
Genomics/Bioinformatics Software Engineer
Candidate would be responsible for developing software to generate benchmark data sets and/or benchmarking methods for NIST human genome reference materials. Ideal candidate would have background and passion in developing open-source research software. Software products would include benchmarking applications such as hap.py (written in combination of C++ and Python) and analysis pipelines written in snakemake, WDL, or CWL. The ideal candidate will have a background and passion for developing open-source research software and understanding of biology with interest in learning about human whole genome sequencing. Ideal background includes development of at least one released open-source software tool/package for bioinformatics, computational biology, computer science, or applied math/statistics in Python, R, C++, or Java or an analysis pipeline in snakemake, WDL, or CWL