Senior Scientist – Cheminformatics & Computational Chemistry

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Cogent IBS, Inc, is seeking the following. Apply via Dice today!

Dear Partner,

Good Morning ,

Greetings from Nukasani group Inc !, We have below urgent long term contract project immediately available for Senior Scientist – Cheminformatics & Computational Chemistry, South San Francisco, CA ,Hybrid need submissions you please review the below role, if you are available, could you please send me updated word resume, and below candidate submission format details, immediately. If you are not available, any referrals would be greatly appreciated.

Interviews are in progress, urgent response is appreciated. Looking forward for your immediate response and working with you.

Candidate Submission Format - needed from you

Full Legal Name

Personal Cell No ( Not google phone number)

Email Id

Skype Id

Interview Availability

Availability to start, if selected

Current Location

Open to Relocate

Work Authorization

Total Relevant Experience

Education./ Year of graduation

University Name, Location

Last 5 digits of SSN

Country of Birth

Contractor Type

DOB: (dd/mm) mm/dd

Home Zip Code

LinkedIn ID

Assigned Job Details

Job Title : Senior Scientist – Cheminformatics & Computational Chemistry

Location: South San Francisco, CA ,Hybrid

Rate : Best competitive rate

Position Overview

We are seeking a highly motivated Senior Scientist in Cheminformatics & Computational Chemistry to design, evaluate, and implement end-to-end computational workflows for small molecule drug discovery within the TuneLab platform.

This role sits at the intersection of cheminformatics, physics-based modeling, and machine learning, and requires strong hands-on expertise across the drug discovery pipeline—from virtual screening to lead optimization. You will collaborate closely with cross-functional teams to develop scalable, production-grade solutions that drive scientific innovation.

This is a high-impact contract role, requiring independent decision-making, including tool evaluation and build-vs-buy assessments.

Key Responsibilities

• End-to-End Workflow Development
• Design and implement computational workflows across the drug discovery lifecycle:
• Virtual screening (ligand-based and structure-based)
• Hit identification and expansion
• Hit-to-lead selection
• Lead optimization
• Method Development & Application
• Apply and integrate advanced computational chemistry and cheminformatics methods, including:
  
  

Ultra-Large Library Search

• Substructure search
• Fingerprint and embedding-based similarity search
• Shape and pharmacophore-based screening
  
  

Molecular Enumeration

• Reaction-based enumeration
• Fragment-based design and expansion
  
  

Ligand-Based Modeling

• QSAR modeling
• Similarity analysis and clustering
• Active learning and iterative design
  
  

Structure-Based Modeling

• Docking, rescoring, and pose prediction
• Structure-aware search techniques
  
  

Physics-Based Methods

• Molecular Dynamics (MD) simulations
• Free Energy Perturbation (FEP) and related approaches

• Cross-Functional Collaboration
• Partner with:
• Machine Learning teams to integrate predictive and generative models
• Software Engineering teams to productionize workflows and ensure scalability
• Scientific stakeholders to align solutions with drug discovery objectives
  

Required Qualifications

• MS or PhD in Cheminformatics, Computational Chemistry, Medicinal Chemistry, or a related field
• 5–10 years of relevant industry experience
• Strong understanding of small molecule drug discovery workflows
• Demonstrated expertise in:
• Substructure and similarity search methods
• Shape and pharmacophore modeling
• Docking and structure-based design
• QSAR and ligand-based modeling
• Active learning methodologies
• Physics-based simulations (MD, FEP)
• Hands-on experience with tools such as:
• RDKit, OpenEye, or equivalent
• Docking platforms (e.g., Glide, AutoDock, GOLD)
• Strong programming skills in Python
  
  

Preferred Qualifications

• Experience working with ultra-large chemical libraries (e.g., Enamine REAL, WuXi Galaxy)
• Familiarity with generative chemistry approaches (SMILES-, graph-, or diffusion-based models)
• Experience integrating machine learning models into production environments
• Knowledge of workflow orchestration tools (e.g., Airflow, Nextflow)
  
  

Best,

Bhavani

Recruiter | IT & Digital Marketing

P:

540 W Galena Blvd, Suite 200

Aurora, IL 60506