Machine Learning Scientist

Columbia University Irving Medical Center; New York (NY); On-site; USD 155,000 - 230,000; Full time

Job summary

A leading medical research institution in New York seeks a Machine Learning Scientist to design neural networks for biomolecular systems. Candidates should have an M.S. with five years of experience or a Ph.D. in relevant fields. The role demands strong programming skills in Python and experience in machine learning. This full-time position offers a competitive salary ranging from $155,000 to $230,000.

Qualifications

• M.S. in related fields with five years of experience or equivalent.
• Ph.D. highly preferred.
• Extensive experience in designing and training neural architectures.

Responsibilities

• Design and train neural network architectures for biomolecular systems.
• Develop active learning algorithms for data acquisition.
• Write code, run experiments, analyze data, and prepare reports.

Skills

Machine learning

Python programming

Data analysis

Collaborative teamwork

Interpersonal skills

Education

M.S. in computer science or related fields

Ph.D. in computer science or related fields

Tools

Neural networks

Job description

Overview

Machine Learning Scientist role at Columbia University Irving Medical Center.

Employer and Job Details

• Job Type: Officer of Administration
• Regular/Temporary: Regular
• Hours Per Week: 35
• Salary Range: $155,000-$230,000

The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University’s good faith and reasonable estimate of the range of possible compensation at the time of posting.

Responsibilities

High-level (dependent on specific scientific project):

• 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.

Day-to-day:

• 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.

Minimum Qualifications

• 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 Qualifications

• 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.

Other Requirements

• N/A

Equal Opportunity Employer

/ Disability / Veteran

Columbia University is committed to the hiring of qualified local residents.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Other
• Industries: Hospitals and Health Care