Adjunct Faculty: MS in Data, Analytics and Policy: Data Visualization and Machine Learning

Johns Hopkins, founded in 1876, is America's first research university and home to nine world-class academic divisions working together as one university.

Description

Johns Hopkins University
Advanced Academic Programs
Data Analytics and Policy Program
Adjunct Faculty: Data Visualization and Machine Learning

Institution Description:
The Advanced Academic Programs (AAP) is a division of the Krieger School of Arts and Sciences at the Johns Hopkins University (JHU). As the nation's oldest and one of the most prestigious research universities, Johns Hopkins offers high-quality master's degrees and post-baccalaureate education to students in the mid-Atlantic region and online. In addition to the online programs, AAP also offers master's degree programs at its Washington, DC Center and at the Homewood campus in Baltimore, MD. AAP has approximately 18,000 enrollments each academic year. JHU is committed to hiring candidates who, through their teaching and service, will contribute to the diversity and excellence of the academic community.

Position Description:
The Advanced Academic Programs (AAP) division seeks one or more non-tenure track adjunct faculty to develop and teach courses within the Master of Science in Data Analytics and Policy program. Specifically, we are seeking instructors qualified to teach Data Visualization (470.673) and/or Machine Learning Methods and Applications (470.667). Applicants may also be considered for other teaching opportunities in the program. The course(s) will begin their development processes in January 2024 and will be taught in the fall 2024 semester and beyond. The courses will be taught fully online (asynchronously) and/or onsite in Washington, DC. Candidates with online course development and teaching experience and those with experience teaching and engaging students from diverse backgrounds are of particular interest.

Data Visualization is a core course in our curriculum, introducing learners to exploratory data analysis and visualization in R, Python, and Tableau. Interactive visualization and dashboard development are also included in the course.

Machine Learning Methods and Applications is an introductory course in machine learning, including topics such as linear modeling for prediction, classification, tree-based methods, support vector machines, and an introduction to deep learning and neural networks.

Full course descriptions and an overview of our full curriculum are available on the program website .

Faculty duties include collaborating with the program director and AAP’s instructional design team on course design in the spring and summer of 2024. In fall 2024, the faculty member will serve as the instructor for the course(s).

Qualifications

Minimum Qualifications

• An advanced degree with training in quantitative methods, with a master’s degree at minimum (e.g., political science, sociology, business analytics, economics, geography, public policy, psychology, or similar)
• Experience with statistical programming, data visualization, machine learning, and data analytics

Preferred Qualifications

• A terminal degree with training in quantitative statistical methods (e.g., political science, sociology, business analytics, economics, geography, public policy, psychology, or similar)
• 1-3 years of graduate or advanced undergraduate-level teaching experience
• Online teaching experience
• Experience or interest in multimedia course content development
• 1-3 years of professional experience with applied statistics, predictive modeling, machine learning, database management, and related data science tools. An equivalent record of scholarly work is also desirable.

Application Instructions

The position will remain open until filled. For best consideration, please apply by August 21, 2023.

Candidates must submit the following:

• Cover letter
• Curriculum vitae
• Teaching evaluations for two most recently taught courses, if the applicant has teaching experience.
• Sample syllabi for relevant data analytics course(s), if available
• transcript for your highest degree awarded

The selected candidate will be expected to undergo a background check and submit references upon request.

Equal Employment Opportunity Statement

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristic. The university is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors that are irrelevant to the program involved.

The successful candidate(s) for this position will be subject to a pre-employment background check.

If you are interested in applying for employment with The Johns Hopkins University and require special assistance or accommodation during any part of the pre-employment process, please contact the HR Business Services Office at jhurecruitment@jhu.edu. For TTY users, call via Maryland Relay or dial 711.

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During the Influenza ("the flu") season, as a condition of employment, The Johns Hopkins Institutions require all employees who provide ongoing services to patients or work in patient care or clinical care areas to have an annual influenza vaccination or possess an approved medical or religious exception. Failure to meet this requirement may result in termination of employment.

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