Scientist I, RNA Machine Learning (t443)

  • Contract Duration: 4++ Months
  • Research & Development
  • San Diego, CA

Website Lenox Executive Search

*This role requires full vaccination against COVID-19 as a condition of assignment, subject to a valid and approved medical or religious accommodation*

•       In silico design of RNA- Oligonucleotide drugs based on RNA structure and/or sequence
•       Analyzing and interpreting with high throughput screening data with machine learning based methods for the development of Oligonucleotide Therapeutics
•       Generate data insights to drive RNA-Oligonucleotide projects; Interface with research teams and support the data analysis and interpretation needs of Oligonucleotide projects

•       Develop and Implement machine-learning based computational pipelines to prioritize oligonucleotide as well as functional impact in diseases
•       Support RNA-Oligo therapeutic teams to identify and validate novel drug targets using advanced computational biology techniques.
•       Independently conduct data analysis tasks within a project scope, exercising judgement to evaluate a variety of statistical factors.
•       Create visualizations, interpret high dimensional data and explain results to cross-functional teams

•       Knowledge of and experience with machine learning and bioinformatic techniques.
•       In-depth knowledge of currently computational methods for Oligo potency prediction
•       Basic scientific understanding of molecular biology and genomics
•       Statistical modeling and machine learning to extract features or rules describing RNA-RNA and RNA-protein interactions
•       Solid knowledge of Unix/Linux, command line interfaces, and fluency in some common scripting and/or programming language (e.g., R, Python, Perl, Java, C / C++), including common machine-learning libraries and framework.
•       Familiarity with parallel computing, relational databases (e.g., SQL) and cloud computing or distributed computing (i.e. AWS)

•       Keeps current with emerging trends in bioinformatics and computational biology
•       Familiarity with popular public domain data sources and programmatic interfaces
•       Experience in designing and conducting computational biology activities to meet program objectives; able to provide input on timelines and resource needs as indicated
•       Independently manages own workload
•       Scientifically independent Interaction (The span and nature of one’s engagement with others when performing one’s job, internal and external relationships)
•       Conducts scientific presentations to internal audiences
•       Excellent problem solving, communication, presentation, and interpersonal skills
Innovation (The required level of scientific knowledge, knowledge sharing, innovation and risk taking)
•       Receives high level instructions on all work, determines methods on new assignments, works closely with manager, may manage junior staff
Complexity (Products managed, mix of businesses, internal and/or external business environment, cultural considerations)

•       PhD degree in a computation biology, bioinformatics, chemistry engineering or similar discipline

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