COVID-19 Information

Department of Microbiology and Immunology

Mission Statement

The Department of Microbiology and Immunology at Dartmouth believes that rigorous teaching and research in the fields of microbiology and immunology are integral to improving health and welfare on a global level. Through the programs in our department we are advancing our knowledge in the fields of infectious disease, inflammation, and immunity while training the next generation of scientists and physicians.

The department values the contribution of diversity to a more just society and innovative science. We will not silently tolerate any form of discrimination in our department. We commit to immediate and ongoing actions to enhance representation and inclusivity and pledge to fight against racial and gender-based injustice both in academia and in the broader community.

We resolve to listen, learn, and educate ourselves about the discrimination faced by people of color and all other under-represented groups. Our Department will take the following actions:

  •     Representation:  We commit to increase representation in our community by recruiting, mentoring, and supporting under-represented groups at all levels of the department and to invite speakers from diverse backgrounds.
  •     Inclusivity: Within our department, we will implement policies that create opportunities for people from diverse backgrounds by promoting their voices and perspectives at departmental activities, such as retreats and career development events. 
  •     Accountability: We will promptly hold accountable anyone who takes part in discrimination or harassment, and support those who speak out against injustice, regardless of rank.


RSS Upcoming Events

  • Data Science and AI Webinar Series July 9, 2020
    Title: Identifying and Modeling Higher Order Lags in Intensive Longitudinal Data Abstract: With the recent growth in intensive longitudinal designs and the corresponding demand for methods to analyze such data, there has never been a more pressing need for user-friendly analytic tools that can identify and estimate optimal time lags in intensive longitudinal data. The […]

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