Assistant Professor, MCBS - AI Biochemistry

University System of New Hampshire; North Carolina; On-site; GBP 82,000 - 127,000; Full time

Benefits offered by this job

Program development opportunities

Collaborative research environment

Job summary

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) to develop and apply AI/ML approaches to advance biochemistry and biomedical science.

The successful candidate will establish an externally funded research program, contribute to undergraduate and graduate teaching, mentor students, and build collaborations

Qualifications

• PhD in a biochemistry, molecular biology, computational biology, bioinformatics, chemistry, CS, data science, bioengineering, or closely related field.
• Evidence of AI/ML method use or development addressing biochemical/biomedical questions.
• Potential to establish an externally funded independent program.

Responsibilities

• Establish and sustain an independent, externally funded research program at the AI/biochemistry interface.
• Develop computational approaches for protein modeling, systems biology, and drug discovery.
• Publish in peer-reviewed journals and present at conferences.
• Mentor students and collaborate across MCBS, COLSA, UNH centers, and partners.

Skills

AI/ML methods

Computational biology

Data science

Biochemistry/molecular biology

Education

PhD in biochemistry or related field

Tools

AI/ML frameworks

Molecular modeling software

Job description

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.

Requirements

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