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As the leader in Decision Medicine™, Pillar’s technology platform drives significantly more efficient and accessible NGS testing with industry-leading accuracy and sensitivity.
Pillar’s extensive portfolio applies across the entire patient journey, from profiling to therapy selection and monitoring, generating actionable insights to get patients on the right therapy faster
In conjunction with the SLIMamp assay technology, Pillar Biosciences has an informatics pipeline called the Pillar Variant Analysis Toolkit (PiVAT) that is not only highly accurate, enabling somatic variant calls down to 1% allele frequency without use of Unique Identifiers (UIDs), but also fast and efficient, returning valuable sample data quickly.
For higher-sensitivity applications such as cell-free DNA analyses, Pillar Biosciences has developed a dedicated assay technology for cell-free DNA that uses UID methodology, to work with the PiVAT pipeline to drive sensitivity down to 0.1%-0.2%.
Our bioinformatics team, working in biostatistics, genomics and bioinformatics in the next-generation sequencing (NGS) domain is expanding. We are searching for a bioinformatics data scientist to focus on design and improvement of PCR assays for high throughput NGS genomic sequencing. This exceptional opportunity offers the chance to work with a team focused on the forefront of genomic and cellular understanding of cancer.
Responsibilities:
Work closely with software, experimental, regulatory, biological and clinical collaborators as a key member of the bioinformatics team in understanding assay performance
Support the PCR primer/probe design. Identifies known and emerging nucleic acid biomarkers (SNV, InDel, DupDel, CNV, methylation, and fusions) via review of scientific papers and clinical trial summaries that drive treatment choices or are useful for monitor disease progression
Analyze and interpret high-throughput internal DNA and RNA sequencing data from designed chemistry, with a specific focus on mutation identification and oncology characterization
Improve biology/oncology understanding and assay performance based on the data.
Qualifications:
MS with 3+ years of experience or PhD in genetics or related discipline
Passionate about bioinformatics and data science
Proven critical thinking capability with ability to follow through
Proven understanding of both human genetics, oncology, and the genetic variation associated with various types of cancer
Well versed with public sequence depositories of genome sequence and variation data, especially those focused on oncology and is able to query, retrieve, manipulate, and analyze data from these databases
Experienced with the development of nucleic acid diagnostics based on the amplification of DNA and RNA via PCR
Excellent communication (written and verbal) and data presentation skills.
Preferred:
Deep knowledge and experience analyzing NGS data on human genome, either from industry or academia
Proficiency with standard NGS tools like bwa, samtools, bedtools, etc.
Experience working with somatic or low input DNA assays
Experience and knowledge of commercially available of modern variant calling packages
Proficient with excel or scripting language to analyze/understand NGS data
Pillar Biosciences aims to "Make precision medicine the first option for every patient" by developing and manufacturing targeted next-generation sequencing (NGS)-based assays and software for today’s high-throughput specialty NGS laboratories. We are seeking collaborative and independent problem solvers to support our mission.
Pillar Biosciences is an Equal Opportunity and Affirmative Action employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; religion; age; nationality; marital status; sexual orientation; disability or any other characteristic protected by law.
Required profile
Experience
Level of experience:Mid-level (2-5 years)
Industry :
Biotech: Biology + Technology
Spoken language(s):
English
Check out the description to know which languages are mandatory.