Molecular Modeling

Molecular Modeling Data Jobs

2 jobs found

2d ago

Data Scientist Cheminformatics and Computational

MD Anderson Houston, TX

Houston, TX

2d ago

$107k - $160k/yr Full time Artificial Intelligence Computational Drug Discovery Data & Ai

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Job Description

Drive AI-augmented drug discovery and development by building and validating cheminformatics and computational chemistry models for cancer therapeutics research.

Responsibilities

Apply generative models to propose chemical matter for targets of interest.
Develop novel methods in coordination with senior scientists.
Develop QSAR/QSPR models using public and internal data.
Rationalize toxicity patterns to support cancer therapeutics discovery.
Propose chemical matter and drug-target interactions to advance discovery efforts.
Document work thoroughly.
Produce research output for scientific publications and contribute to manuscript development.
Present results at multidisciplinary project meetings and external meetings.
Attend collaborator meetings and team working group meetings.
Prioritize and manage multiple projects in a timely, resource-effective manner.
Stay up to date with relevant literature, gather information systematically, and confer with the supervisor regarding new procedures.

Requirements

At least an MSc in Chemistry, Biochemistry, Computer Science, or a related field.
Expertise and comfort with large datasets, plus a willingness to learn new approaches.
Scientific computing skills using Python in a Unix environment, including GPU computing.
Proficiency in generative AI for molecular generation.
Proficiency with PyTorch, rdkit, and other machine/deep learning utilities for cheminformatics.
Familiarity with programmatic access to public databases such as ChEMBL.
Experience using molecular visualization tools, such as PyMol and VMD.
Familiarity with basic statistical testing.
Proficiency in AI/ML-based computational chemistry and cheminformatics is required.

Technologies

AI/ML
Machine learning
Deep learning
Python
Unix
GPU computing
Generative AI
PyTorch
rdkit
ChEMBL
PyMol
VMD

Education

Required: Bachelor’s degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or a related field.
Preferred: Master’s degree in Science, Engineering, or related field; PhD in Science, Engineering, or related field.

Experience

Required: Three years of scientific software or industry development/analysis experience.
With a Master’s degree: one year experience.
With a PhD: no experience required.
Preferred: Computational Chemist.

Compensation

USD 106,500 - 159,500 per year
Minimum salary: USD 106,500
Midpoint salary: USD 133,000
Maximum salary: USD 159,500
FLSA: exempt; not eligible for overtime pay

Benefits

Employer-paid medical coverage starting day one for employees working 30+ hours/week; optional group dental, vision, life, AD&D, and disability insurance.
PTO and Extended Illness Bank accruals, plus paid holidays, wellness, childcare, and other leave options.
Tuition Assistance Program after six months of service; access to wellness, fitness, and employee resource groups.
Defined-benefit pension through the Teachers Retirement System; voluntary retirement plans; employer-paid life and reduced salary protection programs.

Job Details

Employment status: Full-Time
Employee status: Regular
Work week: Days
Work location: Hybrid (Onsite/Remote)
Location: Houston, TX
Fund type: Soft
Pivotal position: Yes
Referral bonus available: Yes
Relocation assistance available: Yes
Requisition ID: 182871

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1mo ago

AI Engineer III – Computational Drug Discovery AI Model Development

Sam Quest Solutions Inc. Remote 🌍 Remote

Remote

1mo ago Closed

$70 - $100/hr Full time Ai Model Training Artificial Intelligence Computational Drug Discovery

This position is no longer accepting applications (closed Sep 20, 2026).

Job Description

Sam Quest Solutions Inc. is hiring an AI Engineer III to help build and refine AI/ML modeling capabilities for computational drug discovery. This role centers on developing, fine-tuning, and benchmarking models that move from protein/ligand sequence inputs to predictions of 3D structure and affinity, supporting multiple lead optimization programs.

In this remote position, you will design automated workflows and evaluate model performance across scientific datasets, with a focus on runtime efficiency and reproducible results. The work includes comparing alternative pose generation and docking approaches and determining how models should be structured for project-specific versus cross-project use.

What you’ll do

Fine-tune pre-trained foundation models such as Boltz-2 and AISB using domain-specific project data
Compile and curate datasets from multiple LO projects, including experimental protein-ligand complex structures and potency or affinity measurements
Analyze dataset variation to stress-test model applicability domains
Benchmark model performance against established methods including DeepAutoQSAR, GatorAffinity, MPNN, MM-GBSA, FEP, and related approaches
Compare co-folder pose generation against docking-based methods
Measure recall and precision using project-specific thresholds and build model ranking based on confidence and applicability domain
Assess whether a single fine-tuned co-folder model can serve multiple projects or whether project-specific models are required
Design an automated, end-to-end workflow optimized to produce single predictions in under a minute using GPU or CPU

What you bring

Strong experience in machine learning, computational chemistry, cheminformatics, or related scientific data science domains
Experience training and fine-tuning models on domain-specific scientific datasets
Experience with 3D modeling workflows, pose generation, or docking-based comparison studies
Working knowledge of benchmarking methodologies and model performance evaluation
Strong Python skills, including scripting and automation
Ability to build reproducible, scalable model workflows with runtime efficiency in mind
Collaboration and communication skills across scientific and technical teams

Technologies

Python
GPU, CPU
Boltz-2, AISB
DeepAutoQSAR, GatorAffinity
MPNN, MM-GBSA, FEP

Compensation and location

Location: Remote
Pay: USD 70 - 100 per hour

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Molecular Modeling Data Jobs

Data Scientist Cheminformatics and Computational

AI Engineer III – Computational Drug Discovery AI Model Development

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