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Senior Scientist - Computational Biology
5000 Shoreline Ct, Suite 300 South San Francisco, CA 94080 US
Job Description
Seeking a contractor at the level of Senior Scientist to join our Computational Biology team. This individual will work on several attributes of our drug and target discovery pipeline including biomarker discovery in late-stage programs, as well as target ID and mechanism of action research for early-stage programs. The role will have a heavy focus on computational analysis of internal and public external multi-omics and CRISPR screening datasets to test and help understand the mechanisms of action of drugs in the pipeline. The ideal candidate will be comfortable working with a range of omics datatypes generated from in vitro and in vivo model systems, and from clinical samples. The ideal candidate will enjoy working collaboratively in a fast-paced environment on a range of challenging and exciting scientific problems. This is a unique opportunity to gain broad computational experience throughout the early stages of drug development and work on cutting edge functional genomic and single cell datasets. What you'll do:
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- Carry out standard and complex differential analyses of omics data amongst a wide array of in vitro, and in vivo samples.
- Work closely with scientists throughout the organization to accelerate and enable testing of hypotheses through computational analyses
- Clearly communicate and present results to project teams and the larger organization
- Develop working knowledge of cancer biology underpinning projects to facilitate communication and more rapid analyses
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- BS, MS, or PhD in Bioinformatics, Computational Biology, or closely associated field.
- Hands-on experience with differential gene expression analyses using RNA-Seq.
- Experience with human NGS datasets and UNIX based bioinformatic tools.
- Proficiency in Python/R data processing and usage of bioinformatic packages.
- Experience with visualization and presentation of complex data.
- Experience with CLI usage of cluster and/or cloud computing resources.
- Working understanding behind linear modeling, regression techniques, and statistical testing.
- Experience in using AI models to increase efficiency.
- Problem solver and self-starter who is passionate about their own career growth and development
- Team player who is comfortable playing supporting or leading roles when necessary
- Clear communicator who can work closely with biological scientists
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- Experience with local LLMs or commercial LLM APIs and utilization in workflows.
- Experience with WGS/WES analyses including mutation calling and variant annotation.
- Experience handling non-NGS -omic datasets (Mass Spec, Olink, Nanostring, etc).
- Experience with functional genomics datasets (e.g. CRISPR screening).
- Experience with Oncology based omics data and data resources such as TCGA and DepMap.
- Experience building and validating machine learning based models with multi-omic data sources.
- Experience with non-linear modeling and optimization techniques.
- Experience with Bayesian methods and causal network modeling.
- Experience developing interactive UIs with python/R/Javascript.
- Familiarity with version control and software engineering best practices.
Equal Opportunity Employer: We are proud to be an equal opportunity employer. We welcome and encourage applications from all qualified candidates regardless of race, sex, gender identity or expression, disability, age, religion or belief, sexual orientation, or any other characteristic protected by applicable laws and regulations. It is our policy not to discriminate against any applicant or employee, and we are committed to fostering a diverse, inclusive, and respectful work environment across all locations in which we operate. We believe that diversity, equity, and inclusion are fundamental to our mission and enhance our ability to serve clients globally. If you have a disability or require any reasonable accommodations during the application or interview process, please inform your recruiter or contact us directly so that we can explore the appropriate arrangements.
Fraud Alert: Candidate safety is a top priority at Planet Pharma. The industry has seen an increase in people falsely representing themselves as recruiters to gather personal information from job seekers. For your safety, do not provide sensitive data to anyone you have not spoken with thoroughly, never provide banking information during the application process and always double check the email address of the Recruiter to ensure it’s from an official Planet Pharma domain (@planet-pharma.com, @planet-pharma.co.uk, and @ppgadvisorypartners.com) and not a domain with an alternative extension like .net, .org or .jobs.
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