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PROGRAM DIRECTOR, MIDS

Master in Interdisciplinary Data Science (MIDS) 

Work Performed:

  • Develop and direct Capstone program, including organizing proposal solicitation and online submission, review of applications, and selection of partners.
  • Work with outside partners to define clear and achievable project goals, and translate those goals into formal agreements.
  • Develop and implement procedures for matching MIDS students and partners.
  • Cultivate, vet, and maintain positive relationships with partners both inside and outside Duke to ensure success of Capstone program and projects.
  • Identify stakeholders who will influence the success of projects and facilitate their engagement and productive involvement with projects.
  • Advise Duke faculty participating in Capstones on all aspects of Capstone program operations.
  • Work closely with Duke and SSRI data security and legal teams to ensure data and legal requirements for Capstone projects are met.
  • Teach – or coordinate instruction for – the Capstone course, which coaches students participating in Capstone projects in project management, teamwork, and leadership skills.
  • Develop policies and processes to ensure that students involved in the Capstone program have the skills required to succeed in all aspects of their Capstone experience.
  • Work collaboratively with students and with colleagues to develop and maintain a culture that exemplifies a shared value for community, and that provides a supportive and stimulating learning environment for all students.
  • Support delivery of student services that attend to the needs of and promote the success of students from underrepresented groups and backgrounds.
  • Develop a process and set of procedures for each Capstone project to follow throughout the year to ensure project is meeting milestones and will succeed.
  • Develop success metrics and strategies for evaluating progress using those metrics.
  • Ensure that all commitments are met on- time, within scope and within budget.
  • Oversee personnel and manage resources required to complete projects successfully.
  • Manage and supervise the day-to-day activities of assigned staff, ensuring proper distribution of assignments and adequate staffing, space and facilities for performance of duties.
  • Create systems and processes to maintain all necessary documentation.
  • Plan budget needs by analyzing Capstone program operations on both a short and long term basis. Identify and recommend priorities and goals for future program needs.
  • Develop and implement new services.
  • Review and refine all program processes each year to increase successful outcomes.Work with the MIDS faculty leadership and with individual faculty working within or with MIDS to supervise the Capstone program and to coordinate with and support other components of the MIDS curriculum. Advise on all aspects of Capstone program operations.
  • Collaborate with SSRI's Communications team to implement communications strategies for the Capstone program, including a framework for communicating and building awareness of the Capstone program with both internal and external constituents. This includes managing the Capstone web site, Capstone marketing materials, and Capstone outreach activities.
  • Promote and support collaborative efforts; develop and maintain working relationships with faculty, deans, department chairs, center and institute directors, and administrators throughout the university to increase and improve faculty engagement and involvement in the MIDS Capstone program.
  • Coordinate related activities, including workshops, colloquia, speakers, and conferences as appropriate, ensuring collaboration with other units and organizations within and outside Duke as needed.
  • Represent MIDS by serving in an advisory capacity to University officials in the absence of the Director.
  • Be responsible for the tactical implementation of the program, ensuring continuous improvement of administrative and logistical operations. As part of this responsibility, document and evaluate the program’s processes and performance, suggest new or improved processes, recommend action plans, identify resources, and share ideas and information with colleagues across the SSRI cores, as well as cultivate relationships with Duke departmental partners to ensure success of the program.
  • Create long and short-term plans for admissions processes, course scheduling, program events and students’ activities, and evaluate the success of these processes and events.
  • Orchestrate the daily activities and operations related to the MIDS program. These daily responsibilities include the planning, coordination, and implementation of operations and activities such as classes, workshops, advertising, special events, staffing, financial and general business matters.
  • Assist the DGS by helping students navigate the integration of the different facets of academic life into a fulfilling and coherent academic and career plan. Do this by responding to student questions and requests, ensuring the highest level of professionalism and customer service for an outstanding level of student services.
  • Coordinate and track faculty-student mentor relationships to ensure student needs and milestones are met.
  • Be the primary point of contact for the students for all non-academic matters, including health concerns and accommodations.
  • Design, budget, implement, and coordinate all logistics for academic and special events including pre-term preparation sessions (boot camps), course review sessions, team building activities, job interview training workshops, other professional development workshops, job fairs, and graduation.

Apply here with Req code: 401522593


ADJUNCT TEACHING POSITION IN DATA SCIENCE

The Social Science Research Institute (SSRI) and the Department of Computer Science at Duke University are jointly seeking applicants for an adjunct teaching position (non-tenure). Candidates must have a PhD in computer science or a related discipline, or industry experience/expertise commensurate with having earned a Ph.D. Specifically, the candidate should have expertise in natural language processing, text mining, information retrieval, and/or related areas, and must be qualified to teach undergraduate and graduate courses on these subjects. The preferred candidate will have college teaching experience, a strong commitment to working with students on projects, the ability and passion to help develop new courses along with any necessary labs, and high personal motivation and responsibility.

The position may start as early as November 2018. 

The main responsibility is to teach one course per semester (for a total of two per year). These will include required and elective courses in text analysis for:

Master in Interdisciplinary Data Science (MIDS) Program, jointly administered by the Information Initiative at Duke (iiD); and Computer Science (CS) degree programs.  

Candidates should supply a letter of interest, curriculum vitae, a teaching statement, and the names of 3 references.

Please email the application materials to ssri-payroll@duke.edu

For more information, please visit: 

Position ID: Duke University-Social Science Research Institute-ADJUNCT [#11677]
Position Title: Adjunct Teaching Position in Data Science
Position Type: Non tenure-track faculty
Position Location: Durham, North Carolina 27708, United States
Subject Area: Data Science
Starting Date: 2018/11/01
Application Deadline: 2018/09/14

Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status. Duke also makes good faith efforts to recruit, hire, and promote qualified women, minorities, individuals with disabilities, and veterans.

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Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual’s age, color, disability, genetic information, gender, gender identity, national origin, race, religion, sexual orientation, or veteran status.

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