Assistant Professor, MCBS-AI Biochemistry

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The College of Life Sciences and Agriculture (COLSA) at the University of New Hampshire (UNH) invites applications for a full-time, tenure-track Assistant Professor in the Department of Molecular, Cellular and Biomedical Sciences (MCBS). We seek an innovative scholar who develops and/or applies artificial intelligence and machine learning approaches to advance biochemistry and biomedical science.

Areas of interest include protein structure, function, and engineering; molecular modeling and simulation; systems biology; multi-omics analysis; computational biochemistry; and AI-enabled therapeutic or drug discovery.

The successful candidate will establish an externally funded research program, contribute to undergraduate and graduate teaching, mentor students, and build scientific collaborations both within and beyond the Department of MCBS.

The position offers opportunities to engage with UNH research infrastructure and collaborative programs, including the Center of Integrated Biomedical and Bioengineering Research (CIBBR), the Hubbard Center for Genome Studies (HCGS), the Research Computing Center, the Data Science Core, and NH-INBRE.

Duties/Responsibilities

Research and Scholarly Activity

• Establish and sustain an independent, nationally recognized, externally funded research program at the intersection of AI/machine learning and biochemistry or biomedical science.
• Develop and apply rigorous computational approaches to biological questions in areas such as protein modeling and engineering, molecular interactions, systems biology, multi-omics, biomarker discovery, or drug discovery.
• Publish research findings in peer-reviewed outlets and present work at scientific and professional meetings.
• Pursue competitive funding from federal agencies, foundations, industry, and other appropriate sponsors.
• Build collaborative research programs across MCBS, COLSA, and relevant UNH departments, centers, and external partners.
• Mentor undergraduate and graduate researchers and support their development as ethical, reproducible, and collaborative scientists.

Teaching, Advising, and Mentorship

• Develop courses and learning modules that integrate artificial intelligence, machine learning, data science, and quantitative reasoning into biochemistry and the life sciences.
• Contribute to existing biochemistry and molecular bioscience curricula and participate in ongoing curriculum development.
• Advise and mentor undergraduate and graduate students, including students engaged in independent research and experiential learning.
• Use evidence-based and inclusive teaching practices that support students with varied academic, cultural, and professional backgrounds.

Service and Professional Engagement

• Contribute service to the department, college, university, scientific community, and relevant professional organizations.
• Participate in faculty governance, student recruitment and retention, program assessment, and other activities that advance the academic mission.
• Help foster a collegial, inclusive, respectful, and team-oriented working and learning environment.

Minimum Acceptable Education & Experience

• A Ph.D. in biochemistry, molecular biology, computational biology, bioinformatics, chemistry, computer science, data science, biomedical engineering, or a closely related field by the appointment start date.
• A record of research accomplishment demonstrating the use or development of AI/machine learning methods to address biochemical or biomedical questions.
• Evidence of the potential to establish an independent, externally funded research program.
• Evidence of the potential for effective undergraduate and graduate teaching, advising, and research mentorship.

Knowledge, Skills & Abilities

• Expertise in AI/machine learning methods relevant to biochemical, molecular, structural, genomic, multi-omic, or drug-discovery research.
• Ability to connect computational methods with biologically meaningful questions, experimental evidence, and reproducible research practices.
• Strong written, oral, and interpersonal communication skills for working with students, collaborators, funding agencies, and professional audiences.
• Ability to work independently and collaboratively in a multidisciplinary research and educational environment.
• Commitment to responsible use of data and AI, including transparency, reproducibility, research integrity, and appropriate attention to bias and limitations.
• Commitment to creating an inclusive and respectful workplace and learning environment.

Preferred Qualifications

• Postdoctoral research experience or equivalent advanced professional experience.
• A strong publication record in AI-enabled biochemistry, computational biology, structural biology, multi-omics, systems biology, molecular modeling, protein engineering, or computational drug discovery.
• Evidence of success in, or strong potential for, securing competitive external funding.
• Experience developing or teaching courses in biochemistry, computational biology, bioinformatics, data science, AI, or machine learning.
• Experience collaborating across computational and experimental disciplines and translating computational predictions into testable biological hypotheses.
• Experience mentoring students or trainees from a range of educational and personal backgrounds.

Applicant Instructions

Applicants should be prepared to upload the following documents when applying online within the My Experience: Resume/CV section of the application: (Maximum of 5 Documents - additional documents can be added to the Application Questions section of the application)

• Resume/CV
• Cover Letter
• Contact Information for 3 Professional References
• Teaching Philosophy
• Research Statement

Additional information

Applications that are missing any of the required items may not move forward for consideration. Additional uploaded documents not requested in the position announcement will not be reviewed.

Compensation Pay Range

$85,000-$95,000 depending on the candidate's qualifications and experience.

The University of New Hampshire is an R1 Carnegie classification research institution providing comprehensive, high-quality undergraduate and graduate programs of distinction. UNH is located in Durham on a 188-acre campus, 60 miles north of Boston and 8 miles from the Atlantic coast and is convenient to New Hampshire's lakes and mountains.

There is a student enrollment of 13,000 students, with a full-time faculty of over 600, offering 90 undergraduate and more than 70 graduate programs. The University actively promotes a dynamic learning environment in which qualified individuals of differing perspectives, life experiences, and cultural backgrounds pursue academic goals with mutual respect and shared inquiry.

Salary Grade

Faculty 01