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