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# Machine Learning Department | CMU | Carnegie Mellon University
Machine Learning Department | CMU | Carnegie Mellon University
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### Virtual Graduate Student Orientation
#### August 28, 2020
We hope you can visit us for our Machine Learning Open House, which begins on March 18, 2020, with a 7:30 PM welcome reception.
We have moved our graduate student orientation to virtual attendance only. Please do not hesitate to
contact us with any questions and concerns regarding our graduate student orientation session.
### Faculty Openings
We started accepting applications on August 1, 2020
### ML@CMU Has Launched
Bringing you the latest research in machine learning and related at Carnegie Mellon University.
###### "A breaktrough in Machine Learning will be worth 10 Microsofts." ~Bill Gates
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## Machine Learning Recent News
## Machine Learning Open House For Accepted Ph.D. Students March 18 and 19, 2021
We hope you can visit us for our Machine Learning Open House, which begins on March 18, 2021, with a 7:30 PM welcome reception.
We have moved our open house to virtual attendance only. Please do not hesitate to
contact us with any questions and concerns regarding our Ph.D. Open House.
## Globally Known in AI & ML
### Since 1997
## Ranked #1
### in Machine Learning & AI U.S. News & World Report 2018
## World Renowned Faculty
### For PhD & Master Programs
## What is Machine Learning?
## A message from Manuela Veloso - Herbert A. Simon University Professor
Machine Learning (ML) is a fascinating field of Artificial Intelligence (AI) research and practice where  we investigate how  computer agents can improve their perception, cognition, and action  with experience. Machine Learning is about machines improving from  data, knowledge, experience, and interaction.
As our society increasingly relies on digital data, Machine Learning is crucial for most of our current and future  applications.
## Apply to a Machine Learning Program
## PhD
## Master's
## Undergraduate
### Calendar
5000 Forbes Avenue
Gates Hillman Center, 8th Floor
Pittsburgh, PA 15213
Questions?:
* ©
  2019
  Carnegie Mellon University
Machine Learning Department
Carnegie Mellon University
5000 Forbes Avenue,
Pittsburgh
,
Pennsylvania
15213
.
N/A
(412) 268-2000
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 ›  Faculty Openings
Faculty Openings in the Machine Learning Department
### Important dates for faculty positions that begin Fall 2025:
* Application Opens:  CLOSED
* Teaching Track early review deadline:  CLOSED
* Application Closes:  January 29, 2025 for Tenure and Research Tracks
New: Teaching Post-Doc position [Open year round]
The Machine Learning Department (MLD) in the School of Computer Science (SCS) at Carnegie Mellon University (CMU) invites applications for our Postdoctoral Teaching Fellowship. This is a one-year position, beginning Fall 2025, with the possibility of renewal for a second year.
We seek PhD graduates with deep understanding of machine learning, data science, and computer science, with a demonstrated interest in teaching, and who aim to gain teaching experience. The Machine Learning Department is uniquely situated to offer both introductory and advanced courses in machine learning. The department’s course offerings draw students at all levels including undergraduates, Master’s, and PhD students, both from within the School of Computer Science and from other disciplines. The individual filling this position will have the opportunity to teach or co-teach lecture courses and to work with faculty to continue developing our curriculum in the rapidly advancing field of machine learning.
We also particularly encourage applications from candidates who have a demonstrated track record in tutoring, mentoring, and nurturing female and underrepresented minority students.
Candidates may start in either the Fall or the Spring. Initial review will be performed on applications received by March 1st, but applications will be considered year round.
Multiple Teaching Track Positions  [**We are currently not accepting applications.**]
The Machine Learning Department at Carnegie Mellon University has openings for Teaching Faculty to deliver our world class educational material to diverse student audiances, and to help evolve the teaching of machine learning within and outside our campus. As the world's first and possibly only academic Machine Learning Department, we occupy a unique position in defining the standard curriculum for the field – one that is used as a template by many other universities. With the increasing societal prominence of machine learning in recent years, demand for our courses continues to grow steeply, and requests for us to serve students beyond our local campus have grown significantly.
The individual filling this position will teach introductory and/or advanced machine learning courses to our current students, and may also help evolve our machine learning curriculum, including developing new online and technology-assisted materials to improve educational outcomes and to extend our reach. They will work closely with the department head and other faculty to develop a strategic plan for taking advantage of new online and technology-assisted educational options over the coming decade. They may also oversee aspects of the educational program, e.g., admissions to our Ph.D. and Masters programs,  and advise undergraduate students majoring in Artificial Intelligence or minoring in Machine Learning.
Candidates should have a Ph.D. with deep understanding of machine learning and a background of demonstrated excellence and dedication to teaching. Candidates must be prepared to teach extensive lecture courses at the advanced undergraduate and introductory/intermediate graduate-level and also be prepared to work with other faculty in the department to establish, improve, and standardize the curriculum.  Research is not required but is supported.
For more information about teaching faculty appointments at Carnegie Mellon, please read the .
Multiple Tenure Track Positions  [**We are now accepting applications for positions starting in Fall 2025.**]
The Machine Learning Department of the School of Computer Science at Carnegie Mellon University invites applications for tenure-track positions at the rank of Assistant Professor, as well as positions at the level of Associate and Full Professor. All areas of machine learning and artificial intelligence will be considered. Applicants are expected to have an active research program and a commitment to teaching excellence.
The Department occupies a privileged position in the world of machine learning, in part as the world's first and possibly only academic Machine Learning Department. The Department has close relationships through shared faculty and active collaboration across the university, especially with the Statistics Department, the School of Public Policy, and other academic units in the School of Computer Science, including the Computer Science Department, Language Technologies Institute, Computational Biology Department, Robotics Institute, Human-Computer Interaction Institute, and Software Engineering, and Societal Computing. We seek applicants who will thrive in this interdisciplinary setting.
Carnegie Mellon is highly supportive of dual career candidates and strongly encourages them to apply.
We also particularly encourage applications from candidates who have a demonstrated track record in mentoring and nurturing female and underrepresented minority students.
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Open Rank Faculty, Delphi Group
We welcome new faculty at any rank and any track (tenure, research, systems, teaching) to join us in leading the Delphi group in the coming decade, to develop and deploy the technology and science that are urgently needed for epidemic tracking and forecasting.  .
| Carnegie Mellon University abides by the requirements of 41 CFR §§ 60-1.4(a), 60-300.5(a) and 60-741.5(a). These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, or national origin. Moreover, these regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, national origin, protected veteran status or disability. |
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# Application Requirements:
* **Cover Letter**
* **Curriculum Vitae**
* **Research Statement***Required: research, tenure and systems track**Optional: teaching track*
* **Teaching Statement**
  *Required: tenure and teaching track positions
            Optional: research and systems track*
* **Broader Impacts Statement**
* **Copies of 3 Representative Papers**
* **Reference Names and Email Addresses**
  *Three or more individuals who have been asked to provide letters of reference.*
# Application Submission
Faculty Positions - Tenure - 
Faculty Positions -  and 
For any questions regarding Faculty Applications, please email:
scs-faculty-search@cs.cmu.edu
Machine Learning - CMU
mldwebmaster@cs.cmu.edu
* © 2025 Carnegie Mellon University
 Machine Learning Department Carnegie Mellon University   5000 Forbes Avenue,
Gates Hillman Center,
8th Floor Pittsburgh, Pennsylvania 15213. ! N/A (412) 268-2000
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## "A bug is never just a mistake. It represents something bigger. An error of thinking. That makes you who you are."~ Elliot Alderson
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 ›  Info for Current Students
| Current ML PhD Student Information     **Reading & Research Groups:** |
| Current MS Student Information  |
| Current Undergraduate Student Information  |
| Contacting Faculty  |
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# Helpful Links
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 ›  PhD Courses & Milestones
# PhD Courses & Milestones (suggested schedule)
| **Fall - Year 1** | **Spring - Year 1** |
| --- | --- |
| 10-715 Adv. Intro to Machine Learning (required core) | 10-716 Statistical Machine Learning (required core) |
| 36-705 Intermediate Statistics (required core) | Menu Core Course |
| 10-920 Reading & Research | 10-920 Reading & Research |
|  |  |
| **Fall - Year 2** | **Spring - Year 2** |
| Menu Core Course | Elective Course\* |
| 10718 ML in Practice (required core) | 10-920 Reading & Research |
| 10-920 Reading & Research | MILESTONE - Speaking Skills should be complete |
| \*Depending on when your chosen elective course is offered, take in either fall or spring. | |
| **Fall - Year 3** | **Spring - Year 3** |
| Complete 1st TA Requirement | Complete 2nd TA Requirement |
| MILESTONE - Courses Complete | MILESTONE - TA Requirement Complete by end of semester |
|  | MILESTONE - Request  if complete |
| **Fall - Year 4** | **Spring - Year 4** |
| Thesis Proposal | 10-930 Dissertation Research |
| 10-920 Reading & Research |  |
| **Fall - Year 5** | **Spring - Year 5** |
| 10-930 Dissertation Research | 10-930 Dissertation Research |
|  | Thesis Defense |
|  | **MILESTONE - GRADUATE!** |