Job Summary (Primary function)
Essential Functions of the Job (Key responsibilities)
- Design, develop and execute biochemical and biophysical assays of various formats to support high throughput confirmation, qualification, and optimization of AI generated hits, including compounds of different affinities and/or of different binding locations towards the target.
- Investigate and elucidate molecular mode of action of compounds of interest.
- Interact and collaborate effectively with both internal and external partners to progress projects towards milestones, including but not limited to, medicinal chemistry group, structural biology group, preclinical pharmacology group, and biologics group etc.
- Contribute to hit/lead discovery and lead-optimization strategies for new targets and new modality.
- Seek, evaluate, and implement new technologies and capabilities to increase speed and quality of early drug discovery.
- Prepare and write technical reports to support drug candidate nomination, internal and external presentations, and publications.
- Potential to lead early drug discovery efforts.
Qualifications (Minimal acceptable level of education, work experience, and competency)
- A PhD in biochemistry, biophysics, or chemical biology with 2+ years industry experience.
- Hands-on experience in developing and running high throughput assays for hit identification and qualification, with one or more target classes, such as enzymes, receptors, and/or protein regulators.
- Industry experience with different molecular modalities in drug discovery, such as enzyme inhibition or activation, protein allosteric modulation, and/or targeted protein degradation.
- Extensive lab-based experience with labeled and label-free assay technologies, such as high-throughput SPR assay and data reduction.
- Solid understanding of the thermodynamic and kinetic principles of ligand protein interaction, protein conformational dynamics, and a clear demonstration of use of that in a drug discovery setting, being able to build and (in)validate kinetic and chemical models of ligand and target interaction.
- Experience with data analysis software, such as Prism, Genedata. Familiarity with data visualization tools such as Spotfire is a plus.
- Experience with cellular target binding assays, and biochemical to cellular activity correlation is a plus.
- Successful candidate should be self-motivated, result-oriented, and has a strong sense of urgency. The candidate shall thrive in a fast-paced, dynamic matrix environment.
- Experience with lab automation and robotics is a plus.
- General knowledge of medicinal chemistry, structural biology and/or disease biology is a plus.
- General knowledge of AI/ML and their applications in drug discovery is a plus.
- Project leadership experience is a plus.
Disclaimer: The above statements are intended to describe the general nature and level of work performed by employees assigned to this job. They are not intended to be an exhaustive list of all duties, responsibilities, and qualifications. Management reserves the right to change or modify such duties as required.
Learn more at:
During the process, you may be asked to respond to questions that will screen out your application if you do not meet certain objective criteria required by the job. You can learn more about this process .
