Details
Title | Preceptor in Computational and Data Sciences |
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School | Harvard John A. Paulson School of Engineering and Applied Sciences |
Department/Area | Computational Science and Engineering and Data Science |
Position Description | The Institute for Applied Computational Science (IACS) in the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) seeks applications for a Preceptor in Computational and Data Sciences. The position is an annual (twelve-month) academic appointment with an expected start date of January 1, 2022. The initial appointment is for three years, with the second and third years contingent on successful review after the first year, followed by a term of up to five years. Preceptors are expected to launch a successful teaching career by developing superior teaching and administrative abilities as part of a team of educators, and the position offers the applicant the opportunity to work closely with Harvard faculty and staff to develop and implement innovative curricula and course material. The Preceptor will collaborate with IACS faculty and staff on teaching, developing, and supporting its courses in computational science and engineering (CSE) and data science (DS) and help to coordinate consistency and coherence across these curricula by creating unified structures for course content and managing web content curation. Duties include: (1) teaching weekly review lectures and leading sections and labs; (2) working with teaching faculty to prepare problem sets, section activities, review sessions, and written examinations and to develop instructional materials and software; (3) overseeing course administration as well as supervising and training teaching fellows; and (4) acting as primary liaison between teaching faculty and the academic computing support group. There are numerous opportunities for the IACS Preceptor to engage with Harvard faculty, students, and scholars in computer science and other disciplines, including the bi-weekly IACS lunch seminar series, the IACS annual symposium, student computational challenge and workshops, and applied computation and applied data science courses, including the project-based capstone course. IACS is the home for students and faculty who are tackling major challenges in science and the world through the use of computational and data science methods. IACS trains graduate students to solve real-world problems by using mathematical models, algorithms, systems innovations, statistics, and machine learning. Embedded within a large liberal arts research University, IACS serves as the focal point for interdisciplinary collaborations in computational science and data science at Harvard and the Boston area community. For more information on the IACS, please visit: https://iacs.seas.harvard.edu/home |
Basic Qualifications | Applicants must have an advanced degree in the broad area of computational and data sciences. |
Additional Qualifications | In addition, we seek candidates who have the teaching experience necessary to assist in a broad range of courses, as well as collaborative skills and expertise in course development, mentoring students, and managing large classes. The position requires initiative, collaborative spirit, and the ability to manage large teams of teaching staff. |
Special Instructions | Required documents include a cover letter; CV; three letters of reference; a two-page statement of teaching interests including a description of teaching/advising experience, and a one-page statement on the applicant’s experience and/or ideas for creating an environment supporting diversity, inclusion, and belonging. All application material (including letters of reference) must be received by October 15, 2021. We particularly encourage applications from historically underrepresented groups, including women and minorities. |
Contact Information | Please contact Program Manager Erin Erhart with any questions. |
Contact Email | [email protected] |
Equal Opportunity Employer | 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. |
Minimum Number of References Required | 3 |
Maximum Number of References Allowed | 3 |
Keywords |
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