An affiliate of Colossal is seeking a talented Senior Research Associate in computational biology with strong analytical skills to tackle challenging genotype-to-phenotype questions. The successful candidate will collaborate with scientists and engineers to perform bioinformatics analyses and integrate genomic, epigenomic, transcriptomic, and proteomic datasets to support Colossal Bioscience's de-extinction efforts. The candidate must have experience in bioinformatics or computational biology.
Preference will be given to candidates with a Masters degree who have experience analyzing and integrating diverse omics modalities (e.g., genomics, epigenomics, transcriptomics, proteomics) using functional annotations and ontologies in the context of data-sparse or non-model organisms.This position will be based on-site in Dallas, TX. Relocation assistance is available.
Duties and Responsibilities:- Run data analysis with biological data
- Run comparative, functional, and statistical genomics analysis
- Develop new tools in R/Python for data analysis and visualization
- Maintain electronic laboratory records and prepare reports or presentations to communicate findings to wet-bench biologists and leadership
Required Skills and Abilities:- Two years of bioinformatics experience in the following areas: Functional Genomics / Multi-Omics, Comparative Genomics, Molecular Evolution, or Applied Statistics in Genomics.
- Capable of leveraging knowledge across multiple levels of biological organization to validate the outputs of complex, integrative analyses.
- Demonstrated 2 years of experience with scripting languages, including but not limited to: Python, R, Perl, Ruby, Java, and BASH.
- Ability to write and run custom bioinformatics scripts using existing published tools and occasionally tools developed to summarize the results in a digestible manner and deliver the information using established reporting procedures.
- Proficiency with handling large-scale genomic data in an HPC (SGE, SLURM, PBS) Linux and/or cloud environment (e.g. AWS, Google Cloud, Azure).
- Experience in using GIT version control software and maintaining well-documented, reproducible notebooks and workflows.
- Ability to design and maintain databases (MySQL, PostgreSQL, MongoDB) and connect with visual platforms to curate and share data with non-bioinformatics team members.
- Self-motivated, proactive, and detail oriented, along with the ability to perform well under pressure and deadlines
- Enthusiasm for learning new skills and taking on new responsibilities
- Strong written and oral communication skills, as well as creative problem-solving skills
- Able to excel in a fast-paced startup environment and participate in team-driven science
Preferred Skills and Abilities:- Executing rigorous analyses of diverse functional epigenomics approaches (e.g., RNA-seq and ATAC-seq) and integrating multi-omics datasets to aid in understanding of gene expression regulation
- Constructing, interpreting, and utilizing pangenome graphs, whole genome alignments, and gene homology relationships
- Familiarity in producing and curating genomic resources (e.g., reference genomes and gene annotations) for vertebrate organisms, especially in non-traditional model systems.
- Experience calling germline and somatic sequence variants from high-coverage WGS, low-coverage WGS with imputation, and sequencing libraries from degraded or ancient DNA
- Understanding of precision gene editing technologies like CRISPR/Cas9 systems
Education and Experience:- Bachelors with 2 years of experience or Masters in quantitative or basic science (computer science, computational biology, bioinformatics, chemistry, physics, or mathematics preferred) is required
What Colossal Offers Full-Time Employees:- Medical, dental, and vision coverage
- Excellent paid time off and company holidays so you can rest and recharge
- Flexible spending accounts (FSA)
- Company matched 401k retirement plan
- Paid parental leave at 100% salary for up to 12 weeks
- Education reimbursement
- An opportunity to help us return the Earth to a healthier state
