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    Sr. Scientist, Sequencing Assay Development - San Diego, United States - BioPhase Solutions

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    Description

    Job Description

    Job Description

    Summary

    This role will be responsible advancing company knowledge of cell and gene therapy sequencing assays through innovative experimental design and efficient execution. The ideal candidate will have a proven track record in successfully developing new sequencing methods, working closely with a multidisciplinary team of engineers and scientists. They will be design and perform experiments using state-of-the-art approaches - integrating cutting edge technology, automation, and data science where appropriate. This role requires excellent communication and creativity, backed by a high level of velocity and rigor.

    Responsibilities

    • Drive innovation through development of new sequencing-based QC platforms and analytics - NGS, WGS, WES, epigenome, transcriptome / RNASeq, single-cell RNA and DNA sequencing (scRNA, scDNA).
    • Design, execute, and interpret data from sophisticated experiments and clearly communicate key findings to teams within Resilience R&D.
    • Perform library preparation and sequencing runs using current and prototype sequencing systems, as required.
    • Perform practical beta-testing of new bioinformatics pipelines and algorithms.
    • Prepare and follow standard operating procedures, batch records, and other process documentation.
    • Analyze and document experimental data in electronic laboratory notebooks in a timely and accurate manner in accordance with the company quality management system.
    • Mentor research associates in proper laboratory techniques and scientific experimental design.
    • Attend and present scientific data to colleagues at internal meetings.
    • Participate in daily Agile stand-ups and weekly sprints with other members of the research team.

    Qualifications

    • PhD degree in Biology, Engineering, Medicine or related discipline with 2-5 years of laboratory research or industry experience.
    • 3+ years of expertise in library design and preparation for complex sequencing programs and/or single cell techniques to enable high-throughput, data-driven laboratory operations.
    • Extensive hands-on experience in Sanger, NGS, and single cell sequencing systems.
    • Familiarity with methods and systems used in biomanufacturing, essential molecular biology and methods such as PCR, purification, gel electrophoresis, sequencing, and high dimensional cell characterization approaches
    • Demonstrated independent problem solving and systematic data-driven experimental design and execution.
    • Demonstrated ability to clearly communicate technical information and roadmaps through written protocols and/or presentations containing clean figures and visualizations.
    • Innovative and analytical thinker with outstanding interpersonal, communication, and leadership skill.
    • Must be highly disciplined and organized, self-motivated and enthusiastic about taking a hands-on approach to collaborative scientific discovery efforts.

    Preferred Experience

    • Expertise in CRISPR and vector design and related annotation tools
    • Expertise in designing PCR and NGS assays for genome engineering
    • Ability to run WGS and RNAseq analysis pipelines
    • Knowledge of and experience with molecular biology and/or synthetic biology experimental approaches
    • Hands-on lab knowledge and experience with current and next-gen genome engineering and sequencing technologies
    • Working knowledge of current and next-gen automation systems, bioinformatics, and machine learning as related to biology
    • Pre-clinical R&D and IND filing for a cell or gene therapy product or technology
    • Knowledge of viral vector design (AAV, Lentivirus, Gamma retrovirus) and vector manufacturing processes.
    • Knowledge of cell therapy QC assays (incoming patient QC, inline viability, potency and release assays).
    • Experience with novel genome editing nucleases and editing characterization methods (off-target analyses).
    • Awareness of large-scale machine learning techniques, graph modeling, Bayesian analytics.
    • Experience in interfacing with laboratory automation (e.g. automated liquid handlers) and data analysis software.
    • Experience with coding and running bioinformatics scripts (Python, numpy, scipy, pandas, jupyter).


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