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.

NOTE: This position is a two-year term-limited appointment.

The laboratories of Dr. Shyamal Mosalaganti and Dr. Herman Fung at the Life Sciences Institute (LSI) are looking for an Artificial Intelligence and Machine Learning (AI/ML) scientist to develop advanced computer vision workflows to support the identification of biomolecules in cryo-electron tomography (cryo-ET) image volumes and to support the registration of multimodal images for automated adaptive microscopy. You will join a vibrant, collaborative research hub and play a role in pushing technological boundaries in multimodal and 3D bioimage analysis. You will report directly to both Dr. Shyamal Mosalaganti and Dr. Herman Fung and will work a hybrid work schedule consisting of 3-4 days onsite and 1-2 days remote.

The Life Sciences Institute explores biological processes, structures and functions at the finest scale to create impact on a global scale.

More information on the Mosalaganti and Fung labs: 

https://www.lsi.umich.edu/science/our-labs/mosalaganti-lab

https://www.lsi.umich.edu/science/our-labs/herman-fung-lab

Experimental responsibilities will include, but not be limited to:

• Develop and implement advanced AI/ML algorithms for image segmentation and registration
• Collaborate with diverse teams in the Mosalaganti and Fung labs to integrate the latest advancements into workflows
• Manage large-scale image datasets for optimal model performance, continuously optimizing and validating models for real-world applications.

Non-experimental responsibilities will include, but not be limited to:

• Effectively document and present latest advancements and technical concepts to the community
• Contribute to manuscript and grant proposal writing

• Ph.D. in Computer Science, Engineering, Biology, or a related field with a focus on machine learning or computer vision
• Minimum 5 years in multimodal image analysis OR deep learning for image analysis

• Minimum 2 years of experience developing semantic or instance segmentation workflows
• Minimum 2 years of experience deploying vision transformers and/or convolutional neural networks
• Proficiency with deep learning frameworks such as TensorFlow, PyTorch, or Keras

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.

This position will be hybrid with the expectations to be onsite (at the Life Sciences Institute) 3-4 days per week, with the ability to work 1-2 days remote. 

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:

• A retirement plan that provides two-for-one matching contributions
• Many choices for comprehensive health insurance
• Life insurance
• Vision, Dental and Legal Insurance
• Flexible spending accounts for healthcare and dependent care expenses
• Family leave options including maternity and parental leave

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.

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.

The University of Michigan is an equal employment opportunity employer.