The Wyss Institute for Biologically Inspired Engineering at Harvard University seeks a talented energetic professional for a leadership position in our Predictive Bioanalytics Initiative.
We are looking for an innovative data scientist with significant expertise in developing and applying machine learning approaches to problems in biology and medicine. Reporting to the Technology Translation Director, you will lead the Institute’s predictive bioanalytics initiative and collaborate with Institute faculty and staff in high-risk, fundamental research and science-driven technology development. In this exciting role, you will be exposed to many different technologies in areas ranging from therapeutics and diagnostics to synthetic biology and materials science. Your goal will be to identify new product solutions and is a unique opportunity to follow your passion either at the Institute or as a future co-founder of a Wyss start-up.
- Develop and apply machine learning approaches to problems and challenges in synthetic biology
- Integrate artificial intelligence approaches with novel human emulation platforms to repurpose existing drugs, discover new therapeutics and disease biomarkers, and gain insight into physiology and disease states in diseases ranging from viral infections and cancer to radiation-induced toxicity
- Participate in envisioning and writing research proposals and reports to funding agencies, providing critical data, figures or information for grant and patent submissions
- Write and collaborate with faculty and other researchers on manuscripts, abstracts and other publications of research findings
- Identify new external collaboration opportunities with the business development team
- Advanced degree in bioinformatics, computational biology, computer science or related field.
- Minimum of nine years of experience with computational data analysis or related experience. Education may count towards years’ experience.
Qualification & Experience:
- Experience with omics data analysis – specifically transcriptomics, proteomics and metabolomics data – as well as artificial intelligence and machine learning approaches
- Proficiency in R, python, or MATLAB. Knowledge of statistical analysis methods like clustering. Fluency with creating and managing large biological databases
- Demonstrated success in leading and working in cross-functional teams. Excellent documentation, analytical, communication, and inter-personal skills
- Hands on experience systems biology approaches – network inference, statistical learning, and genome-scale modeling a plus. Excellent documentation, analytical, communication, and inter- personal skills
Vacancy Type: Full Time
Job Location: New Haven, CT, US
Application Deadline: N/A