Senior Bioinformatics Scientist - Lead NGS & ML Pipelines

Thornton Tomasetti; California; Híbrido; USD 90 000 - 180 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Health coverage

Tuition reimbursement

Career development

Resumo da oferta

Abbott in La Jolla, CA is seeking a Senior Bioinformatics Scientist to lead and contribute to complex genomics projects in the Cancer Diagnostics division. You will design and implement bioinformatics analyses, develop pipelines for germline sequencing, and apply machine learning to improve variant interpretation in a collaborative research environment.

The role includes mentoring junior scientists and driving technical excellence on programs advancing diagnostic assays.

Qualificações

• PhD in bioinformatics, computational biology, CS, math, or related field; or Master’s with 4 years experience.
• 5+ years in bioinformatics in industry or academia.
• 3+ years in medical device/IVD, biotech, or pharmaceutical industry.
• Experience in Linux-based HPC or cloud environments.
• Proficiency in at least three programming or scripting languages.
• Knowledge of NGS/genomics and molecular biology.
• Experience with statistical tools (R, JMP).

Responsabilidades

• Algorithm development to improve germline variant calling.
• Build bioinformatics pipeline prototypes for germline sequencing.
• Develop ML models for variant classification and clinical significance predictions.
• Mentor junior scientists and provide technical guidance.

Conhecimentos

Algorithm development

Bioinformatics pipelines

Machine learning

NGS / Genomics

Formação académica

PhD in bioinformatics

MS in related field with 4+ years

BS in related field with 6+ years

Ferramentas

Nextflow

AWS

Linux HPC

Cloud computing

Descrição da oferta de emprego

Abbott in La Jolla, CA is seeking a Senior Bioinformatics Scientist to lead and contribute to complex genomics projects in the Cancer Diagnostics division. You will design and implement bioinformatics analyses, develop pipelines for germline sequencing, and apply machine learning to improve variant interpretation in a collaborative research environment.

The role includes mentoring junior scientists and driving technical excellence on programs advancing diagnostic assays.