Job Description
Main Responsibilities
We are seeking a highly skilled AIDD/CADD scientist with strong AI‑driven drug evaluation and CADD capabilities to join our team and drive innovation in small‑molecule drug evaluation and development. This role focuses on building, integrating, and applying AI and physics‑informed computational approaches to support decision‑making.
Key responsibilities include:
- Design, develop, and deploy AI‑powered systems for small‑molecule drug evaluation and development, integrating data from chemistry, biology, and structural modeling.
- Apply and extend CADD methodologies (e.g., structure‑based and ligand‑based approaches) to support drug design and evaluation.
- Combine machine learning models with CADD workflows, including virtual screening, molecular property prediction, binding/pose assessment, and developability evaluation.
- Collaborate closely with medicinal chemists, AI scientist, biologists, and project teams to translate scientific hypotheses and project needs into actionable computational strategies.
- Integrate target biology, disease mechanisms, and chemical design strategies to support rational decision‑making.
- Rapidly prototype, iterate, and optimize models and workflows in a fast‑paced R&D environment.
- Contribute to cross‑project AI/CADD platforms that enable scalable, reusable, and decision‑focused drug evaluation capabilities.
Qualifications
Required Qualifications
- PhD or Master’s degree with equivalent practical experience in CADD,Computational Chemistry, Computational Biology, AI, Machine Learning, or a related technical field.
- Hands‑on experience in AI‑based small‑molecule drug evaluation or CADD‑related applications.
- Solid understanding of small‑molecule drug discovery workflows, including hit identification, lead optimization, and decision checkpoints.
- Strong experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX, and scientific computing tools such as NumPy, SciPy, Pandas.
- Experience working collaboratively with chemistry and biology scientists, with the ability to integrate domain knowledge into computational models.
- Strong problem‑solving skills and the ability to learn quickly in a fast‑paced environment.
- Excellent communication skills for cross‑disciplinary collaboration.
Highly Desired Qualifications
Practical expertise in CADD techniques, such as:
- Structure‑based drug design (e.g., docking, binding pose analysis)
- Ligand‑based modeling (QSAR, similarity, pharmacophore concepts)
- Physics‑informed or hybrid ML/physics approaches
Experience in AI models for drug discovery, including graph neural networks, generative models, structure prediction, or property prediction.
Experience in disease biology and target research, with demonstrated ability to link biological context to chemical design and evaluation strategies.
Familiarity with real pharmaceutical R&D decision processes, project milestones, and trade‑offs (e.g., potency vs. ADMET vs. developability).
Experience building tools or workflows that support project teams rather than stand‑alone research prototypes.
**Required Skills: **
Analytical Thinking, Automated Liquid Handling Systems, Bioanalytical Method Development, Bioanalytical Techniques, Clinical Judgment, Data Analysis, Experimentation, Flow Cytometry, Immunohistochemistry (IHC), Research Proposal Development, Scientific Writing, Teamwork, Tissue Culture Techniques, Working Independently
**Preferred Skills: **
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**Employee Status: **
Regular
Relocation:
VISA Sponsorship:
Travel Requirements:
Flexible Work Arrangements:
Not Applicable
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Job Posting End Date:
07/31/2026
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