Bioinformatics Lead (ProteoVant Therapeutics)
Roivant is a global biopharma company improving health by rapidly delivering innovative medicines & technologies to patients. We do this by building Vants nimble, independent, entrepreneurial companies with a unique approach to sourcing talent, aligning incentives, & deploying technology. Roivant recently created a new Vant in Protein Degradation, ProteoVant Therapeutics, through the acquisition of a leading protein degradation company, the investment of its own capital & $200 million of outside capital, as well as the creation of an experienced management team to build ProteoVant into a leading, independent protein degrader company.
ProteoVant Therapeutics is a newly launched development-stage biotech company focusing on the discovery & development of disease-modifying therapies by harnessing natural protein homeostasis processes. We recently acquired numerous novel, protein degrader programs that are in discovery & preclinical development through our acquisition of Oncopia Therapeutics, a protein degradation company initially focused on oncology indications. Our lead program(s) in oncology may enter the clinic as early as late 2021. The company recently secured $200M in funding from SK Holdings in addition to investment from Roivant Sciences.
In addition to ProteoVants preclinical & discovery protein degrader programs & its deep relationship with the lab of Dr. Shaomeng Wang at the University of Michigan, Proteovant is enhancing its drug discovery engine to accelerate development by combining deep drugging expertise with innovative technology platforms including VantAI (Roivants AI platform) & Silicon Therapeutics (Roivants physics-driven drug design platform).
Our current therapeutic focus includes oncology, immunology, & CNS, with planned expansion into additional therapeutic areas in the near future. ProteoVant is rapidly expanding its discovery & development teams in biology, chemistry, biochemistry, DMPK, bioinformatics, toxicology & CMC at many levels. Our R&D organization is primarily located close to major pharmaceutical companies in the Philadelphia area where we are building state-of-the-art labs & office space. We also maintain offices in New York City, with remote work a possibility for certain positions. Please send your resumes or inquiries to email@example.com.
For additional information on ProteoVant please see our one-page overview here
Location: Pennsylvania, USA
Reporting to: Head of Pre-Clinical R&D & Chief Scientific Officer
Position Summary: She/He will lead the computational/statistical genetics effort supporting target identification & patient stratification for oncology, immune-oncology & other therapeutic areas. The candidate will also work in collaboration with scientists in biologics to integrate high-dimensional data such as Next Generation Sequencing (NGS), single-cell sequencing, proteomics, & translational genomic data in support of all stages of Proteovant research & development. She/He will be responsible for analysis of genomic datasets to mine for & identify actionable intervention points for cancer & for patient selection in cancer
Roles & Responsibilities:
- Serve as a key contributor of computational/statistical genetics data-mining strategies, analytical execution & data interpretations supporting drug discovery target identification & validation.
- Devise strategies & deliver results on patient selection and relevant biomarkers by analyzing patient population genetics & genomics data from large-scale databases.
- Identify opportunities to apply the latest advancements in Artificial Intelligence (AI) to solve complex computational/statistical genetics challenges by independent efforts & by collaborating with VantAI
- Influence multidisciplinary project teams in decision-making by mining large-scale data & developing predictive signatures & models.
- Integrate Next Generation Sequencing (NGS), single-cell sequencing, proteomics, and translational genomic data supporting all stages of Proteovant R&D
- Conduct scientific presentations for internal/external audiences.
- Ph.D. or M.Sc. in Computational Genetics or Computational Biology with biotech or pharmaceutical experiences
- Demonstrated ability to interrogate & analyze genotype-phenotype associations, the ability to translate the analysis results into new biological insights, experimental validation proposals.
- Proficient with processing & analysis of high-dimensional RWE, using text-mining & programming tools.
- Strong hands-on programming skills are desired
- Experienced with data visualization tools & creating reproducible workflows.
- Strong communication skills demonstrated with peer-reviewed publications and/or conference presentations.
- Deep curiosity about emerging trends in artificial intelligence & machine learning.