MMCOE

The MassMutual Center of Excellence Postdoctoral Fellowship at the University of Vermont's Complex Systems Center offers early-career scientists a unique experience to tackle open questions related to complex systems and data science that are of utmost importance in science, industry, and society. This postdoctoral fellowship provides a high level of intellectual freedom and the opportunity to work alongside leading academic researchers and industry partners.

Come to beautiful Burlington, Vermont and work in a highly-collaborative, fun, and dynamic research environment. The Vermont Complex Systems Center is a postdisciplinary team of faculty, researchers, and students working on real-world, data-rich, and meaningful complex systems problems of all kinds.

This postdoctoral fellowship will be funded by our groundbreaking data science partnership with MassMutual. The MassMutual Center of Excellence for Complex Systems and Data Science will initiate research projects and programs aimed at better understanding human wellness through data analytics, as well as programming to cultivate a strong pipeline of data science talent.

The initial research project that will be conducted by the MassMutual Center of Excellence Postdoctoral Fellow include study in any of the following areas:

1. Longevity and wellness, including the link between physical and financial health and environmental impacts on wellness. Current research project centered around sleep.
2. Algorithmic fairness, accountability and transparency, which will encompass alternative underwriting data, methods for controlling bias and data ethics.
3. Measurement methodologies for large scale social systems, covering such topics as macroeconomic events, mortality risk and social cohesion, among others.
4. Complex Systems and Data Science.

We will be reviewing applications on a rolling basis for the Postdoctoral Fellowship until October 25 each year.

Benefits

This 2 (possibility to extend to 3 years) year long fellowship (with potential to be elevated to a Research Associate for more senior applicants) comes with a competitive salary, discretionary funds, funds to organize workshops and working groups, professional development, and a generous benefits package. Expected start date is negotiable; the preferred start term is Winter/Spring.

Eligibility Requirements

A Ph.D.(or expected Ph.D.) in a relevant field (Such as, Physics, Mathematics, Computer Science, Statistics, Computational Social Science, Computational Biology, Data Science)

• Exemplary knowledge of data science and computational tools
• Ability to work independently and lead a research project from the ground-up
• Intellectual curiosity and interest in working in a highly-collaborative complex systems science environment

The University of Vermont is an Equal Opportunity/ Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any category legally protected by federal or state law. Applicants are welcome from any region, there are no associated citizenship requirements.

Application Requirements

• Curriculum vitae
• Cover Letter: stating your general research interests and why you feel you would be a good fit for this postdoctoral fellowship, and address your research plan specific to this postdoc and how you would work on health and wellness issues.
• Three letters of recommendation: letters should come from scholars who are very familiar with your work and who you have collaborated with on an academic research project.

The MassMutual Center of Excellence in Complex Systems and Data Science Graduate Fellowship at University of Vermont offers annual graduate fellowships to students enrolled in the UVM Complex Systems Center's MS and PhD in Complex Systems and Data Science. These fellowships offer a unique experience for students to tackle real world health and wellness problems that matter most for science, industry, and society.

Come to beautiful Burlington, Vermont and work in a highly-collaborative, fun, and dynamic research environment. The Vermont Complex Systems Center is a postdisciplinary team of faculty, researchers, and students working at the University of Vermont's College of Engineering and Mathematical Sciences on real-world, data-rich, and meaningful complex systems problems of all kinds.

This graduate fellowship will be funded by our groundbreaking data science partnership with MassMutual. The MassMutual Center of Excellence for Complex Systems and Data Science will initiate research projects and programs aimed at better understanding human wellness through data analytics, as well as programming to cultivate a strong pipeline of data science talent. This fellowship provides an opportunity to work alongside leading academic researchers and industry partners.

The initial research projects that will be conducted at the MassMutual Center of Excellence include study in the following areas:

• Longevity and wellness, including the link between physical and financial health and environmental impacts on wellness.
• Algorithmic fairness, accountability and transparency, which will encompass alternative underwriting data, methods for controlling bias and data ethics.
• Measurement methodologies for large scale social systems, covering such topics as macroeconomic events, mortality risk and social cohesion, among others.

We will be accepting applications for the MassMutual Graduate Fellows cohort each year until February 1 for Fall Admission, and October 15 for Spring Admission.

Eligibility Requirements

• For PhD Fellowship: a completed Master's Degree
• For Master's Fellowship: a completed Bachelor's Degree
• Knowledge of data science and computational tools
• Ability to work independently
• Intellectual curiosity and interest in working in a highly-collaborative complex systems science environment

The University of Vermont is an Equal Opportunity/ Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any category legally protected by federal or state law. Applicants are welcome from any region, there are no associated citizenship requirements.

M. I. Fudolig, L. S.P. Bloomfield, M. Price, Y. M. Bird, J. E. Hidalgo, J. N. Kim, J. Llorin, J. Lovato, E. W. McGinnis, R. S. McGinnis, T. Ricketts, K. Stanton, P. S. Dodds, C. M. Danforth. The Two Fundamental Shapes of Sleep Heart Rate Dynamics and Their Connection to Mental Health in College Students. Digital Biomarkers. 2024. [link]

L. Bloomfield, M. I. Fudolig, P. S. Dodds, J.Kim, J. Llorin, J. L. Lovato, E. McGinnis, R. S. McGinnis, M. Price, T. Ricketts, K. Stanton, and C. M. Danforth. Events and behaviors associated with symptoms of generalized anxiety disorder in first-year college students. PsyArXiv. 2024. [link]

A. O’Leary,T.Lahey, J. Lovato, B. Loftness, A. Douglas, J. Skelton, J. G. Cohen, W. E. Copeland, R. S. McGinnis, E. W. McGinnis. Using wearable digital devices to screen children for mental health conditions: Ethical promises and challenges. Sensors. 2024. [link]

L. S. P. Bloomfield, M. I. Fudolig, J. Kim, J. Llorin, J. L. Lovato, E. W. McGinnis, R. S. McGinnis, M. Price, T. H. Ricketts, P. S. Dodds, K. Stanton, C. M. Danforth. Predicting stress in first-year college students using sleep data from wearable devices. PLoS Digital Health. 2024. [link]

Matthew Price, Johanna E. Hidalgo , Yoshi M. Bird, Laura S.P. Bloomfield, Casey Buck, Janine Cerutti, Peter Sheridan Dodds, Mikaela Irene Fudolig, Rachel Gehman, Marc Hickok, Julia Kim, Jordan Llorin, Juniper Lovato, Ellen W. McGinnis, Ryan S. McGinnis, Richard Norton, Vanessa Ramirez, Kathryn Stanton, Taylor H. Ricketts, Christopher M. Danforth . A large clinical trial to improve well-being during the transition to college using wearables: The lived experiences measured using rings study. Contemporary Clinical Trials. 2023. [link]

J. W. Zimmerman, D. Hudon, K. Cramer, J. St. Onge, M. Fudolig, M. Z. Trujillo, C. M. Danforth, P. S. Dodds. A blind spot for large language models: Supradiegetic linguistic information. ArXiv preprint. 2023. [link]

K. Linnell, M. Fudolig, L. Bloomfield, T. McAndrew, T. H. Ricketts, J. P. M. O'Neil-Dunne, P. S. Dodds, C.M. Danforth. Park visitation and walkshed demographics in the United States. ArXiv preprint. 2023. [link]

K. Minor, K. L. Glavind, A. J. Schwartz, C. M. Danforth, S. Lehmann, A. Bjerre-Nielsen. Nature exposure is associated with reduced smartphone use. Environment and Behavior. 2023. [link]

A. M. Stupinski, T. Alshaabi, M. V. Arnold, J. L. Adams, J. R. Minot, M. Price, P. S. Dodds, C. M. Danforth. Quantifying changes in the language used around mental health on Twitter over 10 years: Observational study. JMIR Mental Health. 2022. [link]

A. J. Schwartz , P. S. Dodds, J. P. M. O’Neil-Dunne, T. H. Ricketts, C. M. Danforth. Gauging the happiness benefit of US urban parks through Twitter. PLoS ONE. 2022. [link]

T. Alshaabi, M. V. Arnold, J. R. Minot, J. L. Adams, D. R. Dewhurst, A. J. Reagan, R. Muhamad, C. M. Danforth, P. S. Dodds. How the world’s collective attention is being paid to a pandemic: COVID-19 related n-gram time series for 24 languages on Twitter. PLoS ONE. 2021. [link]

T. Alshaabi, J. R. Minot, M. V. Arnold, J. L. Adams, D. R. Dewhurst, A. J. Reagan, R. Muhamad, C. M. Danforth, P. S. Dodds. How the world's collective attention is being paid to a pandemic: COVID-19 related 1-gram time series for 24 languages on Twitter. [link]

D. R. Dewhurst, T. Alshaabi, M. V. Arnold, J. R. Minot, C.M. Danforth, P. S. Dodds. Divergent modes of online collective attention to the COVID-19 pandemic are associated with future caseload variance. [link]

P. S. Dodds, J. R. Minot, M. V. Arnold, T. Alshaabi, J. L. Adams, D. R. Dewhurst, A. J. Reagan, C.M. Danforth. Fame and Ultrafame: Measuring and comparing daily levels of `being talked about' for United States' presidents, their rivals, God, countries, and K-pop [link]

H. Mitchell, M. Mahoney, P. S. Dodds, C. M. Danforth. Chimera States and Seizures in a Mouse Neuronal Model. In review. 2019. [link]

D. R. Dewhurst, C. M. Danforth, P. S. Dodds. Noncooperative dynamics in election interference. In review. 2019. [link]

L. Jennings, C. M. Danforth, P. S. Dodds, E. Pinel, L. Pope. Exploring Perceptions of Veganism. In review. 2019. [link]

T. Gray, C. M. Danforth, P. S. Dodds. Hahahahaha, Duuuuude, Yeeessss!: A two-parameter characterization of stretchable words and the dynamics of mistypings and misspellings. In review. 2019 [link]

D. R. Dewhurst, T. Alshaabi, D. Kiley, M. V. Arnold, J. R. Minot, C. M. Danforth, P. S. Dodds. The shocklet transform: A decomposition method for the identification of local, mechanism-driven dynamics in sociotechnical time series. In review. 2019. [link]

B. F. Tivnan, D. R. Dewhurst, C. M. Van Oort, J. H. Ring, T. J. Gray, B. F. Tivnan, M. T. K. Kohler, M. T. McMahon, D. Slater, J. Veneman, C. M. Danforth. Fragmentation and Inefficiencies in US equity markets: Evidence from the Dow 30. In review. 2019. [link]

D. R. Dewhurst, C. M. Van Oort, J. H. Ring, T. J. Gray, C. M. Danforth, B.F. Tivnan. Scaling of inefficiencies in the U.S. equity markets: Evidence from three market indices and more than 2900 securities. In review. 2019. [link]

E. M. Clark, T. James, C. A. Jones, A. Alapati, P. Ukandu, C. M. Danforth, P. S. Dodds. A Sentiment Analysis of Breast Cancer Treatment Experiences and Healthcare Perceptions Across Twitter. In review. 2019. [link]

A. Schwartz, P. S. Dodds, J. P. M. O’Neil-Dunne, C. M. Danforth, T. Ricketts. Visitors to urban greenspace have higher sentiment and lower negativity on Twitter. People and Nature. 2019. [link]

M. Niles, A. J. Reagan, B. Emery, P. S. Dodds, C. M. Danforth. Social media usage patterns during natural hazards. PLoS ONE. 2019. [link]

D. R. Dewhurst, Y. Li, A. Bogdan, J. Geng. Evolving ab initio trading strategies in heterogeneous environments. [link]