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Machine Learning Drug Discovery Postdoc Jobs (NOW HIRING)

Bayer

Principal Machine Learning Scientist

Cambridge, MA · On-site

$123K - $185K/yr

Principal Machine Learning Scientist The Principal Machine Learning Scientist will develop novel ... Identify opportunities for accelerating ongoing drug discovery projects with internal and external ...

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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 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 the key skills and qualifications needed to thrive as a Machine Learning Drug Discovery Postdoc, and why are they important?

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.
Principal Machine Learning Scientist

Principal Machine Learning Scientist

Bayer

Cambridge, MA • On-site

$123K - $185K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted yesterday

Bayer rating

8.1

Company rating: 8.1 out of 10

Based on 65 frontline employees who took The Breakroom Quiz

31st of 71 rated pharmaceutical

Job description

At Bayer we're visionaries, driven to solve the world's toughest challenges and striving for a world where 'Health for all Hunger for none' is no longer a dream, but a real possibility. We're doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining 'impossible'. There are so many reasons to join us. If you're hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there's only one choice.
Principal Machine Learning Scientist
The Principal Machine Learning Scientist will develop novel machine learning algorithms and workflows for accelerating early-stage drug discovery. In this role, you are responsible for constructing, studying, and training algorithms that learn from complex, high-dimensional data to uncover patterns and develop practical predictive models and applications. Involves utilizing various techniques, such as random forests, deep learning, and neural networks, to enhance the predictive capabilities of algorithms, particularly in natural language processing and machine perception. Focuses on simulating human learning activities, improving system performance through data analysis, and developing deep learning frameworks and systems that operate independently of explicit programming instructions. By continuously refining models and exploring new methodologies, contributes to innovative solutions that leverage machine learning for diverse applications.
YOUR TASKS AND RESPONSIBILITIES
The primary responsibilities of the Principal Machine Learning Scientist are to:
  • Develop, evaluate, and apply machine learning algorithms and workflows for accelerating early-stage drug discovery, including but not limited to (i) de-novo design of biomolecules, (ii) assessment of target druggability across therapeutic modalities (iii) design of drug delivery systems, (iv) identification of novel druggable pockets and epitopes, (vi) characterization of protein-protein and protein-ligand interactions;
  • Contribute to the implementation, validation, and improvement of machine learning tools and software solutions that support drug discovery activities;
  • Identify opportunities for accelerating ongoing drug discovery projects with internal and external AI capabilities;
  • Communicate, educate, and engage with a broad set of stakeholders (chemists, biologists, computational/data scientists, R&D leadership) on the state of technology and the progress of key internal initiatives. Engage with the broader scientific community through publications, talks, and open-source;
  • Keep up to date with the latest advances in AI-driven modeling of biomolecular structure and dynamics.

WHO YOU ARE
Bayer seeks an incumbent who possesses the following:
Required Qualifications:
  • Ph.D. degree in Computational Chemistry/Biology, Chem/Bioinformatics, Chemical/Biological/Molecular Engineering, or a related field at the intersection of life sciences and computer science;
  • Deep expertise with state-of-the-art machine learning methods for modeling biomolecules, like co-folding and/or generative methods for protein design;
  • Expertise in handling, processing, integrating and analyzing large datasets related to drug development research, including biochemical, biophysical, and structural biology data;
  • Strong programming skills in Python;
  • Demonstrated commitment to scientific rigor, a track record of scientific excellence, strong analytical thinking, and a high degree of self-motivation;
  • Excellent written and verbal communication.

Preferred Qualifications:
  • 5+ years of relevant post-PhD experience, including 2+ years in industry;
  • Experience with established, physics-based protein modelling methods like Molecular Dynamics and/or Rosetta;
  • Experience in coordinating small, interdisciplinary teams and ability to articulate their impact to managerial stakeholders;
  • Strong record of publications or patents related to machine learning solutions for biomolecular modeling.

Employees can expect to be paid a salary between $123,760.00 - $185,640.00. Additional compensation may include a bonus or commission (if relevant). Additional benefits include healthcare, vision, dental, retirement, PTO, sick leave, etc.
This salary range is merely an estimate and may vary based on an applicant's location, market data/ranges, skills, prior relevant experience, certain degrees and certifications, and other relevant factors.
This posting will be available for application until at least 04/17/2026.
YOUR APPLICATION
Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Health for all, Hunger for none, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer.
To all recruitment agencies: Bayer does not accept unsolicited third party resumes.
Bayer is an Equal Opportunity Employer/Disabled/Veterans
Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.
Equal Opportunity Employer Statement: Notice for U.S. Visitors: All information on this site is subject to compliance with local rule and regulations as they may vary from time to time and across different geographies, including, without limitation, U.S. Executive Orders. Bayer is an E-Verify Employer. Location:United States : Massachusetts : Cambridge Division:Pharmaceuticals Reference Code:865491 Contact Us Email:hrop_usa@bayer.com

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About Bayer

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Bayer is a global enterprise with core competencies in the life science fields of healthcare and nutrition. We design our products and services to help people and planet thrive by supporting efforts to address the unprecedented global challenges presented by a growing and aging global population. At Bayer, we’re committed to drive sustainable development and generate a positive impact with our businesses. Through bold ideas and unprecedented insights, we’re pioneering new possibilities that advance life for all of us. That means reimagining how we care for ourselves and one another by empowering everyday health, improving approaches to patient care, and finding better ways to nourish our communities around the world.

Industry

Agriculture

Company size

10,000+ Employees

Headquarters location

Whippany, NJ, US

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