Senior Computational Chemist - ML-Driven Drug Discovery

Scorpion Therapeutics; South Dakota; Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Hybrid work model

Collaborative multidisciplinary teams

Job summary

Scorpion Therapeutics Senior Expert I, Data Science in computational drug discovery focuses on structure-activity relationships, structure-based and ligand-based design, and predictive modeling for small molecule drug development. Lead design efforts integrating machine learning, physics-based CADD methodologies, and experimental data.

Collaborate across disciplines to inform target validation, lead optimization, and candidate nomination; drive hypothesis generation for small molecules,

Qualifications

• PhD in medicinal chemistry, computational chemistry, cheminformatics, or related field.
• 2+ years post-graduate experience in drug discovery.
• Proficiency with computational tools like Schrödinger, OpenEye, high-performance computing.
• Strong publication record preferred.
• Excellent communication and visualization skills.

Responsibilities

• Lead design efforts integrating machine learning, physics-based CADD methodologies, and experimental data.
• Collaborate across disciplines to inform target validation, lead optimization, and candidate nomination.
• Drive hypothesis generation for diverse modalities including small molecules, peptides, RNAs, and protein degraders.
• Support mechanistic studies using biophysical and cellular validation techniques.

Skills

Machine learning

Data analysis

Communication

Visualization

Education

PhD in medicinal/computational chemistry or cheminformatics

Tools

Schrödinger

OpenEye

HPC

Job description

Scorpion Therapeutics Senior Expert I, Data Science in computational drug discovery focuses on structure-activity relationships, structure-based and ligand-based design, and predictive modeling for small molecule drug development. Lead design efforts integrating machine learning, physics-based CADD methodologies, and experimental data.

Collaborate across disciplines to inform target validation, lead optimization, and candidate nomination; drive hypothesis generation for small molecules,