Faculty, Instructor and Fellowship positions beginning 2018
Application Deadline for all positions is December 1, 2017.
Applications for all positions will be accepted via mathjobs, which will open on 10/1/17, and should be complete by the deadlines to receive full consideration.
If a disability or other circumstance prevents you from applying online, please contact our HR Coordinator, Kimberli DeMayo (firstname.lastname@example.org), to arrange an accommodation.
Assistant Professor and Higher
Positions are available in Pure and Applied Mathematics, and Applied Probability at the level of Assistant Professor or higher. Appointments are based primarily on exceptional research qualifications. Appointees will be expected to fulfill teaching duties and pursue their own research program. Position begins September 2018. PhD required by employment start date.
C.L.E. Moore Instructor (in Pure Mathematics)
Instructor (in Applied Mathematics or Statistics)
These positions are open to mathematicians who show definite promise in research. Applicants with PhDs after January 2017 are strongly preferred. Appointees will be expected to fulfill teaching duties and pursue their own research program. Position begins September 2018.
The CLE Moore Instructor position is a full-time, three-year position. The position normally carries a teaching load of four standard recitations each academic year. A standard recitation meets twice weekly for one hour. Depending on the Department's teaching needs, Instructors may teach a course counting as two recitations.
Instructors may take a one-year unpaid, benefits-ineligible leave of absence during the three-year term of the Moore appointment. However, the appointment may not be extended beyond the original three-year term.
American citizens and permanent residents are eligible (and encouraged) to apply for an NSF postdoctoral fellowship. The Moore Instructor position may be combined with an NSF Postdoctoral Fellowship in several ways. Two possibilities are:
- spreading one year of the NSF fellowship over a two-year period by combining it with a half-time appointment as a Moore Instructor. In each of these years the teaching load is reduced to 3 standard recitations
- taking the second year of the NSF fellowship at MIT after the Moore instructor appointment ends
The Applied Mathematics Instructor position is a full-time, two-year position. The position normally carries a teaching load of four standard recitations each academic year. A standard recitation meets twice weekly for one hour. Depending on the Department's teaching needs, Instructors may teach a course counting as two recitations.
Instructors may take a one-year unpaid, benefits-ineligible leave of absence during the two-year term of the Applied Math Instructor appointment. In some cases, the appointment may be extended for a third year beyond the original two-year term. As with the Moore instructorship, Applied Mathematics Instructors who are also the recipients of an NSF fellowship may combine their fellowship with their instructorship.
Digital Learning Fellow (Postdoctoral Associate)
Reporting to the Digital Learning Scientist in the Department of Mathematics, the MITx Digital Learning Fellow will work closely with Faculty to develop course curricula for residential and global modules leveraging the edX and MITx platforms.
The MITx Digital Learning Fellow will work with educational staff to develop courses that include learning objectives, detailed content outlines, measurable outcomes, interactive activities, engaging video, and thoughtful discussion forums. He or she will assist in designing the assessments to test the efficacy of the content in these courses. The MITx Digital Learning Fellow will also assist in teaching courses in a blended context to students on campus as well as in a virtual context to students around the world. He or she will be responsible for developing and launching courses on time, on budget, and to MIT quality standards.
MITx Digital Learning Fellows report to a MITx Digital Learning Scientist and are expected to actively participate in the Digital Learning Lab Community of Practice and will attend regular cross-departmental DLL meetings. As needed the Digital Learning Fellow will work with MITx and edX support services on any course development issues that arise during course development.
MITx Digital Learning Fellow Experience and Qualifications:
- Advanced degree (Ph.D. or Graduate level) in field of applied math, math, mechanical engineering, physics or related field
- Minimum of 2 years relevant teaching experience for college-level courses
- Demonstrated experience as an instructional designer or course developer
- Proven track record of delivering projects on time and within budget
- Demonstrated knowledge of best practices, current research, and innovations in digital teaching and learning in higher education
- Strong project management, time management, and communication skills are essential, as well as the ability to work independently and with a team
- The desire to learn new skills
- Experience creating plots and 3D interactive images in Mathematica or MATLAB preferred
- Experience using Adobe tools and video editing software (Illustrator, Photoshop, After Effects, Premiere) a plus
- This is for a one-year appointment conditional on performance (pending department/ODL agreements)
MIT is an Equal Opportunity, Affirmative Action Employer.