Nonclinical Research and Development | Mountain View, CA | Full Time
Job Description: Scientist II/Biochemistry
Do you want to grow a company that positively impacts the world? twoXAR is seeking an enthusiastic, motivated, and capable individual with expertise in enzymology, biochemistry, assay development and compound screening. Core responsibilities include biochemical assay development, small molecule lead series screening and routine testing of compounds in a variety of assays. The successful candidate will have a PhD and extensive knowledge and experience in the drug discovery and optimization process, with at least 3 years of experience working as a Research Scientist in a drug discovery organization. The successful candidate will work as part of a collaborative team of scientists with expertise in protein production and biophysics supporting hit-to-lead, lead-optimization, and IND candidate selection for various drug discovery programs.
twoXAR is an AI-driven drug discovery and development company focused on first-in-class small molecules. The company currently has a development portfolio of over 18 diseases. twoXAR saves years in drug development while generating a 30x hit rate at in vivo efficacy milestones over traditional methods. We have established collaborations with leading biopharmaceutical companies and are now scaling the business and building our internal drug pipeline. twoXAR is venture-backed with financing from SoftBank Ventures and Andreessen Horowitz and has strong ties to Stanford University and MIT. Our management team and advisory board have decades of biopharmaceutical management experience, built software systems used by tens of millions of people, held VP and C-level positions at Fortune 100 companies, and have had previous startups with successful strategic acquisitions.
Work with Nonclinical R&D team and CROs in identifying, designing in vitro biochemical assays validate assay development and qualification for screening of small molecules synthesized during hit-lead and lead optimization stages.
In collaboration with CROs and group members, design protein constructs for use in biochemical assays.
Contribute to evaluation, optimization and assist in management of external biology CRO resources
Be able to troubleshoot, develop technical solutions and optimize experiments at CROs for robust data output
Carefully document research workflows, data and protocols.
Capture experimental results in database.
Prepare data summaries and reports for sharing with twoXAR Nonclinical R&D and management teams
Work with Nonclinical R&D teams to prepare data summaries and reports needed for IND preparation and submission
Deep knowledge of molecular biology, biochemistry, and the drug discovery process, particularly lead validation through lead optimization stages
Strong problem-solving and data analysis skills
Ability to handle multiple projects simultaneously and meet aggressive project timelines
Excellent interpersonal skills with the ability to engage effectively with various levels of working teams and management.
Excellent written and verbal communication skills.
Proactive, highly motivated, and comfortable working in a fast-paced, evolving environment
Ph.D. in enzymology, biochemistry, molecular or cell biology or related discipline with 3-5 years of industry experience.
Expertise in in vitro biochemical assay design and development in multiple enzyme formats (FRET, FP, fluorometric, colorimetric, ELISA, etc.), medium-throughput compound library screening, and testing of small molecules for determining inhibition/binding.
Application of mathematical binding/inhibition models to determine small molecule mechanism of action (cooperativity, competitive/non-competitive, etc.).
Experience in developing and utilizing biochemical screening assays to support drug discovery lead optimization programs
Proficient in relevant programs for data analysis and visualization, e.g. GraphPad Prism, Microsoft Excel, Microsoft PowerPoint, Microsoft Word
Experience working with CROs to manage assay design, execution, and data analysis