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Machine Learning Computational Biology Jobs (NOW HIRING)

Computational Biology MLOps Engineer

San Diego, CA · On-site

$118K - $139K/yr

You bridge cutting edge AI research and production systems at the intersection of machine learning, computational biology, and high performance computing. You thrive in cross functional environments ...

... machine learning objectives. Requirements Candidates must have : * Either: * PhD in computational biology, AI/ML, applied statistics, biophysics, or , * MS and professional experience in relevant ...

You will join the Bioresilience Incubator, a dynamic engineering center that integrates predictive computational modeling, machine learning, and experimental biology to advance national security and ...

You will join the Bioresilience Incubator, a dynamic engineering center that integrates predictive computational modeling, machine learning, and experimental biology to advance national security and ...

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Machine Learning Computational Biology information

What is a machine learning computational biology?

A Machine Learning Computational Biology job involves applying machine learning techniques to analyze biological data, such as genomics, proteomics, and medical imaging. Professionals in this field develop algorithms and models to identify patterns, make predictions, and generate insights that can drive scientific discovery or improve healthcare. They typically work with large datasets, employing statistical and computational methods to solve complex biological problems. The role often requires expertise in programming, data science, and domain-specific biological knowledge. It is commonly found in academia, pharmaceutical companies, biotech firms, and healthcare institutions.

What types of projects might I work on as a machine learning computational biology specialist?

As a Machine Learning Computational Biology specialist, you may work on projects ranging from analyzing large-scale genomic data to developing predictive models for disease risk or drug response. Typical tasks include designing and implementing machine learning algorithms to identify patterns in biological datasets, collaborating with biologists and clinicians to interpret results, and contributing to publications or presentations. You'll often be part of a multidisciplinary team, interacting with data scientists, laboratory researchers, and software engineers. This role offers the opportunity to work on cutting-edge biomedical research and have a direct impact on advancements in healthcare and life sciences.

What are the key skills and qualifications needed to thrive in the machine learning computational biology position, and why are they important?

To thrive as a Machine Learning Computational Biology professional, you need a strong background in biology, statistics, computer science, and machine learning, typically supported by an advanced degree in a relevant field. Familiarity with programming languages such as Python or R, experience with bioinformatics tools, and knowledge of machine learning frameworks like TensorFlow or scikit-learn are commonly required. Strong analytical thinking, effective communication, and the ability to work collaboratively in interdisciplinary teams are highly valued soft skills. These qualifications are essential for solving complex biological problems, developing robust computational models, and effectively communicating findings to both technical and non-technical stakeholders.

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What job categories do people searching Machine Learning Computational Biology jobs look for?

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Infographic showing various Machine Learning Computational Biology job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Full-time

Re-posted 27 days ago


Job description

Job Summary:
Columbia University Irving Medical Center is seeking a Machine Learning Scientist focused on deep learning models for biomolecular systems and drug discovery. The role involves developing neural network architectures, designing active learning experiments, and collaborating with team members and industry partners.
Responsibilities:
• Design and train state-of-the-art neural network architectures for biomolecular systems, including prediction of protein-ligand, protein-protein, and antibody-antigen structures and affinities, and protein conformational ensembles.
• Design active learning algorithms and experiments to steer large-scale data acquisition campaigns focused on improving biomolecular models.
• Devise experiments to understand scaling behavior of biomolecular models.
• Curate and prepare datasets, and develop dataset processing algorithms, for in-acquisition and proprietary datasets, including in federated training settings.
• Develop new ideas, write code, run experiments, analyze data, and prepare reports.
• Be an active member of one or more highly collaborative teams.
• Stay current with the ultrafast-paced nature of biomolecular machine learning.
• Maintain and enhance external visibility through publishing papers, writing open-source code, and engaging with the scientific community.
Qualifications:
Required:
• M.S. in computer science / machine learning, computational biology, or related quantitative fields plus five years of related experience, or equivalent combination of education/experience.
Preferred:
• Ph.D. in computer science / machine learning, computational biology, or related quantitative fields.
• Extensive machine learning experience, including design, training, and deployment of complex neural architectures.
• Extensive programming experience in Python.
• Strong interpersonal skills, excellent written and verbal communication, and the ability to work effectively in cross-functional teams.
Company:
Columbia University Irving Medical Center is a clinical and educational enterprise that offers medical, dental, and nursing services. It is a sub-organization of Columbia University. Founded in 1767, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.