Research Scientist - Military Veterans

Job Summary

The Museum of Comparative Zoology is seeking a Research Scientist to collaboratively design high-throughput imaging systems for specimen-based data, based on experience collecting and analyzing specimen-based data and literature best practices. Develop and apply matching analytical tools to manage, parse, and analyze specimen-based data generated by these high-throughput specimen digitization platforms. This includes developing algorithms for specimen morphometrics, statistical analysis, and predictive modeling of specimen taxonomy or functional traits as well as developing intuitive data hosting and visualization solutions that increase the usability of these data. The Museum of Comparative Zoology aims to be an inclusive environment that welcomes colleagues of all backgrounds to work in a respectful and collegial environment. Candidates will interact with researchers, students, and the public and we seek candidates who value all these interactions.

Position Description

• Work with others to research and design complex imaging system components and capabilities, and tailor data management and analysis platforms to match.
• Develop and implement algorithms for automatically extracting, parsing and interpreting diverse specimen label metadata.
• Design and implement new protocols for high-throughput specimen data collection using developed imaging system pipelines. Use collected data to refine imaging system hardware design and analytical pipelines.
• Provide supervision and training for others to learn and use high-throughput specimen data collection pipelines, supervising the expansion of the imaging pipeline to mass digitization across the museum. Responsible for the completion of functional digitization solution objectives.
• Apply statistical methods and machine learning techniques to analyze large specimen-based datasets and identify patterns and correlations.
• Create predictive models to infer functional data, such as taxonomic identity, sex, or other functional traits (e.g. chemical composition) from specimen spectral and morphological data.
• Work with museum staff across departments to ensure that extracted morphometrics, traits and metadata are useful and relevant across a broad range of specimen taxa and morphologies.
• Collaborate with affiliated faculty, researchers and museum staff on long range plans to translate analytical findings into actionable insights for conservation and scientific research, such as identifying morphological diversity hotspots as conservation targets, or identifying species with unique morphologies for further study.
• Develop and maintain intuitive, user-friendly data hosting and visualization solutions for analytical prediction algorithms and extended specimen data.
• Document analytical processes and develop user guides for data analysis tools and collaborate with other working group members on authoring publications in academic journals and presenting research findings at conferences.
• Identify funding opportunities, prepare grant proposals, and secure funding from diverse sources to support and expand high-throughput imaging and digitization initiatives.

Basic Qualifications

• A minimum of a Master's degree in Biology, Evolution or Ecology, Bioinformatics, Data Science, Biostatistics, or a related field.
• 5+ years experience in big data analytics, statistical modeling, and machine learning.
• 5+ years direct experience working with collections and specimen-based data and metadata.

Additional Qualifications and Skills

• PhD in Biology, Evolution or Ecology, Bioinformatics, Data Science, Biostatistics, or a related field preferred.
• Extensive experience with statistical and programming languages such as R, Python or MATLAB, or Bash linux.
• Excellent analytical and problem-solving skills.
• Strong communication and collaboration abilities.
• Relevant scientific publications or patents on collections-based imaging system and analytics development.
• Strong background in specimen-based morphometrics and trait extraction.
• Experience applying state of the art machine learning and artificial intelligence algorithms in specimen-based functional trait prediction.
• Demonstrated capacity for writing and obtaining successful grant proposals, and a proven ability to seek out and secure funding from diverse sources, such as government agencies, private foundations, industry partnerships, and philanthropic organizations.
• Proven record of successful collaboration and networking.
• Experience with team management for collections-based research.
• Experience with implementing analytical solutions using high performance computing environments.

Additional Information

To be considered for this position, a cover letter and resume must be submitted.

This is a one-year term position from the date of hire. Harvard University will not provide visa sponsorship for this position.

***All formal offers will be made by FAS Human Resources.

The Harvard Museum of Comparative Zoology (MCZ) is a preeminent center for contemporary zoological research and teaching. Its permanent collections comprise approximately 21 million specimens of extant and fossil invertebrates and vertebrates, as well as frozen tissues, microscope slides and other associated objects, such as the Blaschka glass invertebrates.

We invite individuals with diverse backgrounds, experiences, and abilities to be a part of our community.

Benefits
We invite you to visit Harvard's Total Rewards website ( https://hr.harvard.edu/totalrewards ) to learn more about our outstanding benefits package, which may include:

• Paid Time Off: 3-4 weeks of accrued vacation time per year (3 weeks for support staff and 4 weeks for administrative/professional staff), 12 accrued sick days per year, 12.5 holidays plus a Winter Recess in December/January, 3 personal days per year (prorated based on date of hire), and up to 12 weeks of paid leave for new parents who are primary care givers.
• Health and Welfare: Comprehensive medical, dental, and vision benefits, disability and life insurance programs, along with voluntary benefits. Most coverage begins as of your start date.
• Work/Life and Wellness: Child and elder/adult care resources including on campus childcare centers, Employee Assistance Program, and wellness programs related to stress management, nutrition, meditation, and more.
• Retirement: University-funded retirement plan with contributions from 5% to 15% of eligible compensation, based on age and earnings with full vesting after 3 years of service.
• Tuition Assistance Program: Competitive program including $40 per class at the Harvard Extension School and reduced tuition through other participating Harvard graduate schools.
• Tuition Reimbursement: Program that provides 75% to 90% reimbursement up to $5,250 per calendar year for eligible courses taken at other accredited institutions.
• Professional Development: Programs and classes at little or no cost, including through the Harvard Center for Workplace Development and LinkedIn Learning.
• Commuting and Transportation: Various commuter options handled through the Parking Office, including discounted parking, half-priced public transportation passes and pre-tax transit passes, biking benefits, and more.
• Harvard Facilities Access, Discounts and Perks: Access to Harvard athletic and fitness facilities, libraries, campus events, credit union, and more, as well as discounts to various types of services (legal, financial, etc.) and cultural and leisure activities throughout metro-Boston.

Work Format
On-Site

Commitment to Equity, Diversity, Inclusion, and Belonging
Harvard University views equity, diversity, inclusion, and belonging as the pathway to achieving inclusive excellence and fostering a campus culture where everyone can thrive. We strive to create a community that draws upon the widest possible pool of talent to unify excellence and diversity while fully embracing individuals from varied backgrounds, cultures, races, identities, life experiences, perspectives, beliefs, and values.

EEO Statement
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions, or any other characteristic protected by law.