Associate Principal Scientist, Systems Biology Full-time

Associate Principal Scientist – Systems Biology

The Vaccines & Advanced Biotechnologies department, part of our Research & Development Division, is looking for a passionate and talented systems biologist with expertise in the generation and analysis of complex multi-dimensional and multi-scale biological data to join our research team and support our Company's discovery & development efforts at West Point, PA.

In this role, you will be at the very leading-edge of therapeutic research and development, developing and implementing experimental and computational tools in a dynamic and scientifically rigorous environment. You will operate in a highly collaborative and matrixed organization and engage with cross-functional teams of experimental and computational biologists, data scientists, and colleagues across our Company's ecosystem to drive a diverse therapeutic pipeline.

The successful candidate will be a scientifically curious team player and self-motivated learner with previous knowledge of functional genomics-driven experimental strategies at the bulk and single-cell scales and an interest in developing and using technology solutions (algorithms/tools/etc) to aid in our interpretation of complex biological data.

An ability to communicate clearly and collaborate effectively with colleagues from different disciplines will be essential.

This role is based at our West Point, PA location.

In this exciting role, you will:

• Directly contribute to multiple stages of therapeutic development through rigorous design and/or implementation of high-dimensional functional genomics and cellular profiling assays, including in vitro and in vivo pooled/arrayed CRISPR screens, single-cell transcriptomics and lineage tracing, as well as experimental and in silico derived proteomic datasets.
• Perform statistically rigorous quantitative analyses while employing reproducible research and data integrity practices on large-scale biological datasets.
• Analyze, interpret, and summarize complex biological data and employ data visualization tools to facilitate communication of findings to broader audiences.
• Identify, analyze, and integrate internal and external data and knowledge resources to enable data mining in a biological context and inform actionable learnings to drive pipeline development.
• Develop and implement experimental and/or computational methods to integrate findings from functional genomics screens and other data sets (including RNA-Seq, DRUG-seq, WGS, CRISPR, single cell RNA-Seq, proteomics, and metabolomics) with additional biological data streams to generate deep biological knowledge and drive innovation.

Represent Systems Biology Expertise in Cross-Functional Teams:

• Provide clear interpretation of high-dimensional data and propose candidates for further computational and biological interrogation.
• Engage with cross-functional teams to translate biological hypotheses into experimental and/or computational interrogations of functional genomics data as well as multi-omics molecular profiles to drive iterative experimental design decisions.
• Work in a highly collaborative environment, tightly embedded in project teams across scientific disciplines and functions, bringing together genetics, chemistry, pharmacology, as well as molecular and cellular biology to accelerate the development of therapeutics.

Expand Your Knowledge and Grow Your Career:

• Survey relevant literature on novel experimental and computational methods and introduce them into in-house portfolio of workflows.
• Keep up to date on project-relevant literature (experimental and analytics topics in functional genomics space, specific disease biology, etc) and attend relevant conferences.
• Further your professional development by participating in workshops and seminars aimed at personal and professional growth.

Required Education and Experience:

• Ph.D. in Systems Biology, Computational Biology, Computer Science, Biostatistics, Genetics, Immunology, Mathematics, Molecular Biology, Statistics, or related field and 4 years of experience.
• Experience can be a mix of relevant academic or industrial experience.

Required Experience and Skills:

Applied Experience:

• Demonstrated experience with experimental and/or computational strategies and interpretation of large-scale biological data such as various sequencing modalities, pooled/arrayed CRISPR-based screens.
• Demonstrated fluency with generation and/or analysis of diverse large-scale NGS experimental datasets (e.g., RNAseq, WES, scRNAseq, spatial transcriptomics, etc).
• Demonstrated experience with statistical hypothesis testing methodology and machine learning concepts and methods.
• Experience with integrating results generated from multiple data sources (e.g., different 'omics data sets), and biological knowledge bases to extract meaningful biological insights.

Technical Skills:

• Fluency with experimental and/or computational methods for generating and interrogating high-dimensional biological data. Programming skills with application in statistical analysis (e.g., R, Rshiny, tidyverse, Python, MATLAB), and ability to distill complex data into interpretable visualizations.
• Experience with cell culture, RNA/DNA extractions, preparation of sequencing libraries, molecular biology tools, experimental design strategies.
• Experience with HPC, AWS cloud computing infrastructure and Linux environments.
• Experience with version control systems, such as Git (e.g., Github). Ability to adapt to and work with existing analytic frameworks.

Preferred Experience and Skills:

• Understanding the pros and cons of various algorithms for DNA-seq, RNA-seq, single-cell RNA-seq and/or functional genomics data.
• Familiarity with the data and analytic capabilities of public repositories.
• Familiarity with public databases, and repositories of DNA, RNA, protein, single-cell, as well as functional genomics data.
• Experience extracting meaningful biological insights from high-dimensional biological readouts.
• Strong publication record.

Required Skills:

Bioanalytical Analysis, Bioanalytical Techniques, Biomarker Development, Cell Cultures, Computational Biology, Creativity, CRISPR-Cas System, Data Visualization, Detail-Oriented, Immunology, Mass Spectrometry Analysis, Metabolomics, Molecular Biology, NGS Data Analysis, NGS Technologies, Pipeline Development, Project Management, Proteomics, RNA Sequencing, Scientific Writing, Single-Cell Genomics, Statistical Analysis, Systems Biology

Preferred Skills: