Job Description

How to Apply

A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.

Job Summary

The Life Sciences Institute is looking for a drug discovery scientist with expertise in computational methods to partner with the Director of Michigan Drug Discovery in advancing drug discovery research at the University of Michigan (U-M).

With its administrative home in the Life Sciences Institute , Michigan Drug Discovery (MDD) is a campus-wide program created to support and fund drug discovery research at the University of Michigan. MDD provides ongoing funding for drug discovery projects and provides advice to investigators engaged in drug discovery research broadly defined. MDD staff participate in development discussions and help identify opportunities for U-M investigators to work with external partners.

You will report to the Director of Michigan Drug Discovery and be a resource for U-M investigators. In your role, you will support a broad range of scientists and projects. Flexibility, communication, and the ability to prioritize work will be important.

Mission Statement

The Life Sciences Institute explores biological processes, structures and functions at the finest scale to create impact on a global scale. With a diverse community of inquisitive minds and exceptional tools, we are a catalyst for breakthrough discoveries.

For more information on Michigan Drug Discovery:

Responsibilities*

We are looking for driven and collaborative individuals that can fulfill the following tasks:

• Provide computational chemistry support for drug discovery projects such as molecular modeling, structure-based design, and dataset analysis.
• Conduct virtual library development, virtual screening, docking and molecular dynamics for small molecules and their macromolecular targets.
• Be an expert user of molecular modeling tools and a resource for other users on campus.
• Support screening campaigns with DNA-encoded libraries through triage and development of machine learning (ML) models.
• Maintain current awareness of and facility with using state-of-the-art machine learning methods in computational drug discovery, especially those that are available through opensource platforms.
• Evaluate project feasibility, estimate project timelines, and independently prioritize tasks.
• Track time spent on individual projects to provide appropriate recharge data to the financial team.
• Collaborate in the preparation of reports, presentations, and publications.

Required Qualifications*

• A Bachelor's degree in medicinal chemistry, biophysics, computational chemistry, or a related field
• Minimum of 5 years of experience in molecular modeling, structure-based drug design and virtual screening to support drug discovery projects
• Minimum of 5 years of experience selecting, cleaning, and deploying large datasets to build machine learning models in support drug discovery
• Project management skills to prioritize and organize work across multiple projects in parallel
• Ability to communicate verbally and in writing with a broad range of scientists across multiple disciplines

Desired Qualifications*

• Master's or PhD in computational chemistry, medicinal chemistry, biophysics, data science or a related field
• Experience providing computational chemistry support to drug discovery teams
• Collaborative mindset with experience working in multidisciplinary research environments
• Ability to use Python, R or other scripting language for data analysis and workflow automation
• Ability to reduce open-ended discovery questions into meaningful experiments
• Experience applying machine learning methods in drug discovery

Modes of Work

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes .

Additional Information

You will work a hybrid work schedule, which will consist of on-site work being performed in the Life Sciences Institute in Ann Arbor with flexible scheduling and remote work opportunities as made available by LSI policies and as based on program and business needs.

Benefits at the University of Michigan

In addition to a career filled with purpose and opportunity, The University of Michigan offers a comprehensive benefits package to help you stay well, protect yourself and your family and plan for a secure future. Benefits include:

• Generous time off
• A retirement plan that provides two-for-one matching contributions
• Many choices for comprehensive health insurance
• Life insurance
• Dental, Vision and Legal Insurance
• Flexible spending accounts for healthcare and dependent care expenses
• Maternity and Parental Leave

Background Screening

The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks are performed in compliance with the Fair Credit Reporting Act.

Application Deadline

Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.

U-M EEO Statement

The University of Michigan is an equal employment opportunity employer.

Job Detail

Job Opening ID

264185

Working Title

Computational Chemist Lead

Job Title

Chemist Lead

Work Location

Ann Arbor Campus

Ann Arbor, MI

Modes of Work

Hybrid

Full/Part Time

Full-Time

Regular/Temporary

Regular

FLSA Status

Exempt

Organizational Group

Life Sciences Inst

Department

Life Sciences Institute-Admin

Posting Begin/End Date

5/28/2025 - 6/11/2025

Salary

$90,000.00 - $100,000.00

Career Interest

Research

Job Tags

Full time, Temporary work, Part time, Remote job, Without location, Flexible hours,

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