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Machine Learning Drug Discovery Postdoc Jobs (NOW HIRING)

SupportFinity™

Machine Learning Engineer

Boston, MA · On-site

... machine learning, and proprietary big data infrastructure. We are expanding the team of talented ... drug discovery with creativity and innovation. About the Role We are seeking a high-impact Machine ...

Virginia Tech

Postdoctoral Associate

Blacksburg, VA · On-site

Responsibilities : • Developing and applying AI methodologies to drive advances in drug discovery ... discovery and/or AI-driven biomolecular modeling and/or scientific machine learning. Company

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Machine Learning Drug Discovery Postdoc information

What is a machine learning drug discovery postdoc?

A Machine Learning Drug Discovery Postdoc is a postdoctoral researcher who uses advanced machine learning techniques to accelerate and improve the drug discovery process. They work at the intersection of computational science, biology, and chemistry to develop algorithms that can predict molecular properties, identify potential drug candidates, and optimize compounds. Their research helps pharmaceutical companies and academic labs find effective drugs more efficiently, often reducing the time and cost required for new drug development. Typically, these postdocs collaborate closely with interdisciplinary teams and may also contribute to scientific publications and conferences.

What are the key skills and qualifications needed to thrive as a machine learning drug discovery postdoc?

To thrive as a Machine Learning Drug Discovery Postdoc, you need a strong background in computational biology, machine learning, and chemistry, typically supported by a PhD in a relevant field. Expertise with programming languages (such as Python or R), deep learning frameworks (like TensorFlow or PyTorch), and bioinformatics tools is highly valuable. Strong analytical thinking, collaboration, and effective scientific communication are crucial soft skills for advancing research projects and sharing results. These skills and qualities are essential to drive innovation, interpret complex biological data, and translate computational models into actionable drug discovery insights.

What are some typical challenges faced by a machine learning drug discovery postdoc, and how can they be addressed?

As a Machine Learning Drug Discovery Postdoc, one of the main challenges is integrating complex biological data with advanced computational models to generate meaningful insights for drug development. Addressing issues such as data sparsity, heterogeneity, and ensuring model interpretability are common hurdles. Collaborating closely with wet-lab scientists, bioinformaticians, and other computational researchers is essential for validating predictions and translating findings into actionable experiments. Regular communication with interdisciplinary teams and staying updated on the latest computational techniques can help overcome these challenges and drive impactful research.

What are popular job titles related to Machine Learning Drug Discovery Postdoc jobs?

For Machine Learning Drug Discovery Postdoc jobs, the most frequently searched job titles are:

Infographic showing various Machine Learning Drug Discovery Postdoc job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior AI Scientist - Drug Discovery & Computational Biology (Hybrid - Boston, MA, USA)

Boston, MA • On-site

OMG Technology
See more jobs at OMG Technologyexternal

$75/hr

Contractor

Re-posted 6 days ago

Job description

Senior AI Scientist – Drug Discovery & Computational Biology (Hybrid - Boston, MA, USA)
We are looking to hire a candidate with the mentioned skill sets and experience for one of our clients within the Healthcare Industry. This is a 6+ month contracting role, with potential for extension. This is a HYBRID role.


Key Responsibilities:


We are seeking a highly skilled professional with deep expertise in applying Artificial Intelligence and Machine Learning to drug discovery and development. The ideal candidate will have experience in Drug Discovery & Computational Biology (Must).

The candidate should demonstrate a strong track record of leveraging advanced computational approaches to accelerate therapeutic discovery and possess the ability to collaborate effectively with multidisciplinary research and development teams.


Required Skills/Qualifications:


  • Deep expertise in applying Artificial Intelligence and Machine Learning to drug discovery and development.
  • Experience in Drug Discovery & Computational Biology (Must).
  • AI and machine learning methodologies for drug discovery, including predictive modeling, lead optimization, and translational research applications.
  • Graph machine learning techniques for biological networks, molecular property prediction, target identification, and knowledge graph-based discovery.
  • Virtual cell screening and AI-driven target discovery platforms, with particular focus on rare disease research and therapeutic innovation.
  • AI-driven molecular design for small molecules and biologics (Abs/VHH), including toxicity prediction, off-target assessment, developability analysis, and candidate optimization.
  • Structural biology, including protein structure analysis, molecular interactions, computational modeling, and integration of structural data into drug discovery workflows.
  • Healthcare Domain experience (Must).
  • Ability to collaborate effectively with multidisciplinary research and development teams.


Other Job Details:


  • Job Type: C2C or W2.
  • Duration: 6+ months with high possibility of extension.
  • Pay Rate: $75/hr. on C2C or $65/hr. on W2.
  • Location: Hybrid - Boston, MA, USA.
  • Interviews: Video interviews.
  • Docs required: ID proof will be required.