.Job Scope & Purpose:
Our newest, emerging partner in the field of mRNA is seeking a Director, Computational Biology to lead and drive their proprietary mRNA platform. This team is developing the next generation of mRNA therapies that has increased selectivity and critical applications in oncology and immune-oncology. The ideal candidate will have extensive experience within computational biology, bioinformatics and molecular biology. Additionally, the candidate will have a proven track records of successfully driving computational projects while leading FTEs and cross functional teams.
Primary Job Responsibilities:
- Lead a team of highly skilled computational biologists and data scientists
- Apply advanced statistical methods to cross-validate and evaluate significance of hypotheses
- Work collaboratively with internal and external cross-functional teams, collaborators, and SAB members to align, plan and execute on the overall research and development plans
- Work independently and think out of the box to extract meaningful insights from public datasets
- Present scientific findings internally and externally at key scientific conferences
- Support IP filings and manuscript preparations
Primary Job Requirements:
- Ph.D. in Computational Biology/Bioinformatics with 7+ years of Biopharma experience
- Experience in managing a computational biology team
- Preferred experience with NGS data, genomics, transcriptomics, proteomics analyses, bash/shell scripting, public datasets, such as TCGA and GTEX, RNA folding
- Fluency in commonly used programming languages in common computational biology tools, such as Python, R, Perl or C/C++
- Good understanding of capabilities and limits of the modern machine learning techniques such as Deep Neural Networks, CNNs, GANs, LSTMs, and expert knowledge in at least one deep learning framework such TensorFlow or PyTorch
- Familiarity with the heuristic search and multi-objective optimization algorithms such as gradient descent, A-star, genetic algorithms, Bayesian optimization, etc.
- Preferred skills: Theoretical understanding ribosome profiling and network biology, hands on expertise on single-cell transcriptomics, proteomics analyses, massively parallel reporter assays, workflow management, AWS, Azure, or Google Cloud, RNA folding, pathway analysis, and/or machine learning and data visualization experience on biological datasets
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