Best Accredited Universities for Doctoral Phd program in Industrial Engineering

MS in Business Analytics is a full time program that accepts applications for fall term start.

MS in Financial Engineering is a full time program that accepts applications for fall term start.

MS in Management Science and Engineering is a full time program that accepts applications for fall term start.

MS in Operations Research and MS in Industrial Engineering can be full time or part time, with fall and spring start dates.

PhD in Industrial Engineering and Operations Research Program is a full time program that accepts applications for fall term start.

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The preferred background for students entering the program is a bachelor or a master degree in engineering, science, or mathematics. Entering students will need to have studied the following topics in mathematics and statistics as preparation for core courses in the first year of the program. Therefore, applicants who have not yet studied these topics should register for the appropriate courses during the year in which they apply.

At the level of Ross, A First Course in Probability, Pitman, Probability, or Durrett, The Essentials of Probability: random variables, probability distributions including binomial, geometric, Poisson, exponential, and normal, independence, covariance, conditional probability, conditional expectation, the central limit theorem.

It is best to take a theoretical mathematics course in which students learn to do rigorous proofs. A course in real analysis at the level of Rudin, Principles of Mathematical Analysis is the ideal preparation. However, it is not necessary to take it before enrolling in the program, because PhD students can take Math 321-1 Real Analysis at Northwestern in the fall of their first year.

Students should be familiar with computer programming in some language before enrolling in the program, but the particular language is not important. C++, Java, Python, and MATLAB are often used by our students.

View the admissions handbook for the Industrial Engineering and Management Sciences.

The Industrial Engineering and Operations Research (IEOR) offers four graduate programs: a Master of Engineering (MEng), a Master of Science (MS), a Master of Analytics (MAnalytics), and a PhD. This knowledge applies to complex systems in the industrial, service, or public sectors, including energy systems, chains, healthcare systems, and financial systems. Students may concentrate on theoretical studies in preparation for doctoral-level research, or on applications of state-of-the-art techniques to real world problems.

The MEng is a professional, full-time, accelerated professional master degree program. Students learn advanced techniques in IEOR and skills that prepare them to lead teams in developing new engineering solutions: skills in managing complex projects, motivating people, and directing financial and operational matters.

The MS is a full-time technical master degree program. Students focus on both the theory of IEOR techniques and the application of those techniques. The MS is a terminal degree, meaning that students enrolled in the MS program do not typically continue further into the IEOR PhD program. Participants in the program are self-funded the IEOR does not offer funding and students will not be eligible for ASE (academic student employment) appointments funded by the department.

The 11-month in-person Master of Analytics program trains students in data-driven analytical methods and tools for optimization, statistics, simulation, and risk management with relevant industry context so that the graduates are not only highly skilled in the latest tools and fluent with working with large data sets, but also are able to raise the right questions to develop innovative models and find creative solutions to rapidly changing business and industry challenges, and communicate and implement their solutions.

The paramount requirement of a doctoral degree is the successful completion of a thesis on a subject within Industrial Engineering and Operations Research. Research areas may include the investigation of the mathematical foundations of and computational methods for optimization or stochastic models, including risk analysis. Research also may be undertaken to develop methodologies for the design, planning, and or control of systems in a variety of application domains, including chains, energy systems, healthcare systems, and financial systems.

The following minimum requirements apply to all graduate programs and will be verified by the Graduate Division:.

If the applicant has completed a basic degree from a country or political entity (e.g., Quebec) where English is not the official language, adequate proficiency in English to do graduate work, as evidenced by a TOEFL score of at least 90 on the iBT test, 570 on the paper-and-pencil test, or an IELTS Band score of at least 7 on a 9-point scale (note that individual programs may set higher levels for any of these) and.

The Graduate Council views academic degrees not as vocational training certificates, but as evidence of broad training in research methods, independent study, and articulation of learning. Therefore, applicants who already have academic graduate degrees should be able to pursue new subject matter at an advanced level without the need to enroll in a related or similar graduate program.

Applicants with doctoral degrees may be admitted for an additional doctoral degree only if that degree program is in a general area of knowledge distinctly different from the field in which they earned their original degree.

Applicants may apply only to one single degree program or one concurrent degree program per admission cycle.

Unofficial transcripts must contain specific information including the name of the applicant, name of the school, all courses, grades, units, degree conferral (if applicable).

Letters of recommendation: Applicants may request online letters of recommendation through the online application system. Hard copies of recommendation letters must be sent directly to the program, by the recommender, not the Graduate Admissions.

Evidence of English language proficiency:All applicants who have completed a basic degree from a country or political entity in which the official language is not English are required to submit official evidence of English language proficiency. However, applicants who, at the time of application, have already completed at least one year of full-time academic course work with grades of B or better at a US university may submit an official transcript from the US university to fulfill this requirement. The following courses will not fulfill this requirement:.

Courses conducted in a language other than English,.

Courses that will be completed after the application is submitted, and.

Official TOEFL score reports must be sent directly from Educational Test Services (ETS). Official IELTS score reports must be sent electronically from the testing center to University of California, Berkeley, Graduate Division, Sproul Hall, Rm 318 MC 5900, Berkeley, CA 94720. TOEFL and IELTS score reports are only valid for two years prior to beginning the graduate program at UC Berkeley. Note: score reports can not expire before the month of June.

Step II: After passing the preliminary or entrance exam, students prepare for their PhD oral qualifying examination. This step lasts one to two years. With the successful passing of the orals, students are advanced to candidacy for the PhD degree.

Step III: Students undertake research for the PhD dissertation under a three-person committee in charge of their research and dissertation. The students then write a dissertation based on the results of this research. On completion of the research, workshops, and approval of the dissertation by the committee, the students are awarded the doctorate.

Every doctoral student is required to take the doctoral entrance examination. Students entering without an MS degree are required to complete all MS degree requirements and may do so by completing the MS course requirements and passing the doctoral entrance exam.

The entrance examination will be offered near the end of every spring semester, approximately one week before finals. Passing the entrance examination is based on both superior performances on all parts of the exam, and on previous coursework. Students are required to take the entire exam at the same time. In order to take the exam, students are expected to perform sufficiently well in their first-year courses.

In particular, students who enter in the fall are expected to take the exam at the end of the spring semester in the same academic year.

Students who have not taken these courses prior to entering the graduate program are required to do so during their first year.

Some students have specific research interests and goals when they enter a doctoral program for others, these interests develop in the process of taking courses and preparing for the entrance examination. In either case, it is imperative that students begin their research as soon as possible after completing their entrance examination.

A minimum of nine graduate courses is required in the major, including those taken prior to the entrance examination. Usually, these are courses taken in this department, but to a very limited extent, courses taken in other departments or at other institutions may be counted as part of this requirement. These courses should provide depth in the student probable research area.

In addition, course work is required in two minor areas. This loose wording reflects the diverse needs of the College. In this department, each minor must consist of six units at the graduate level, at least three of which must be taken for a letter grade. A minor may serve either to strengthen theoretical foundations (e.g., measure-theoretic probability theory), or as an area of application (e.g., transportation). At most one course of one minor can be a course from within this department, as long as this course is distinct from the major. Graduate courses at other institutions may make up part of a minor if the subject matter is appropriate.

In addition to English, the program does not require another language.

Students are expected to take the Qualifying Examination within three semesters after passing the Doctoral Entrance Exam. Priority in department funding (especially NRTs) will be given to students who have passed their Doctoral Entrance Exams and are in their 3rd, 4th, and 5th semesters. Although it is necessary for a student to identify a potential research area and some potential dissertation topics in order to complete this exam, it is not necessary for the student to do a substantial amount of research in the area of the examination.

The student is required to have completed or be currently enrolled in courses that will complete at least one of the two minors at the time of the Qualifying Examination. At least one of the minors completed or being completed at the time of the Examination must consist entirely of courses from outside the department. In addition, at the time of the Qualifying Examination, the student is required to have a specific plan for completing the other minor within two semesters.

At least six weeks prior to the approximate date of the Qualifying Examination, the student needs to begin to arrange for Graduate Division approval of the exam committee. Once the date and the exam committee are decided upon, the student must also request a room in which the exam can be held. Meanwhile, the student should prepare a list of topics, called a syllabus, which will form the basis of the Exam. The syllabus should include topics from the three subject areas to be listed on the Application for Qualifying Examination form, i.e., equivalent to several courses, together with topics from one of the minor areas.

For students who follow these guidelines and the recommendations of the Graduate Adviser and Thesis Adviser, this usually results in quick approval. However, if preparation is judged to be inadequate, they may recommend additional course work and postponement of this Examination.

In many departments, including IEOR, it has been the practice for students to schedule their own Qualifying Examinations. This exam is to be scheduled for three hours, at a time when all Committee members can attend.

If the student performance is judged to be unsatisfactory, the Committee may recommend reexamination, possibly after additional preparation has been completed. If the reasons for the unsatisfactory performance are judged to be major and fundamental, the Committee may recommend that a second attempt be denied.

The IEOR strives to provide every student with an opportunity to gain teaching experience.

It provides the department an opportunity to review the progress of students who have passed the qualifying examination, toward completion of their doctoral dissertation.

During the workshop, the candidate is expected to present a prospective of, and results from, the dissertation research. Dissertation advisers should advise students the appropriate time for the workshops. However, initiation of the workshops is the student responsibility. The student needs to notify the department at least one month in advance of the desired workshop date, and coordinate this date with the dissertation committee. At least two weeks prior to each workshop, the student shall distribute to the dissertation committee a report called the dissertation prospectus. Announcement of the workshop will be made through all the channels used to announce departmental seminars.

Each workshop is divided into two parts. The first part is devoted to a public presentation by the student and subsequent discussion. (Graduate students who have not yet reached this stage in their own program often find that participating in workshops is a valuable educational experience.) The dissertation committee moderates the presentation and discussion, controls the asking of questions by the audience, and calls an end to the first part of the workshop.

At this time, the committee may decide that the candidate progress is unsatisfactory. The committee may require an additional workshop sooner than one year after the unsatisfactory one. Recurrent failure to present a satisfactory prospectus workshop may result in the disqualification of the student and termination of doctoral candidacy.

A completed copy of the thesis must be distributed to the committee at least two weeks before this final workshop. This workshop will follow the same format as other workshops. The committee will inform the candidate any remaining problems or issues with the thesis. If the committee has serious issues with the thesis, it may require an additional defense workshop.

Students are required to complete 24 semester units of upper division and graduate coursework, 12 units of which must be graduate courses in the major taken for a letter grade. IND ENG 298 units do not count towards this requirement.

Beyond these requirements, the program is quite flexible. No than two units of IND ENG 299 may be counted toward the degree. The remainder of the program can include electives outside the department. In addition, they are expected to have completed at least one semester each of upper division courses in probability and in statistics. They should also have competency in a scientific programming language.

Select two from the following (at least one must be a Modeling course):.

Industrial and Commercial Data Systems (fulfills Modeling requirement).

Students may complete the requirements by writing a thesis, rather than taking a comprehensive examination. The course requirements under the thesis option are the same as under the comprehensive option. Under the thesis option, the minimum unit requirement of regular course work is 20 units, not including the thesis.

In addition to course and waiver exam requirements, students are required to complete one of two options: a comprehensive exam or a master project and oral presentation of this project.

Students who are interested in earning a PhD should apply to enter the MS PhD if they do not yet have an MS degree. detailed information on the entrance exam may be found on the Doctoral Degree Requirements tab.

Minimum number of units to complete degree: 25 semester units.

Technical Course work (must be taken for a letter grade):.

Core Courses: All students are required to take IND ENG 240 and IND ENG 241. Students in the FinTech and IPES programs are also required to take IND ENG 242.

FinTech students must select two of the following: IND ENG 221, IND ENG 222, IND ENG 223 IND ENG 224. IP Entrepreneurship Strategy students must take IND ENG 242 and one additional approved INDENG 200+ course, plus two business courses, ENGIN 273 and ENGIN 274.

Leadership Courses (must be taken for a letter grade).

All students must complete 8 semester units of core leadership courses, which must be in the 200-series.

Students must take the capstone integration course each semester.

Special Topics in Industrial Engineering and Operation Research ( (Fundamentals of Machine Learning Data Analytics)).

Minimum number of units to complete degree: 29-semester units.

All students are encouraged to take a Python boot camp (50 hrs in August) in preparation for the technical coursework. The Python boot camp is a 0-unit course offered in August leading up to the program start.

All students must complete four units of the summer internship (individual study) course (10 weeks in May-July) during the final summer semester.

Expand all course descriptions [+]Collapse all course descriptions [-].

Terms offered: Prior to 2007 This introductory course provides students with sufficient background in Python programming language for use in analytics applications as well as potentially conducting research in the area. The course is designed to prepare students for the applied analytics problems and projects they will encounter in advanced analytics courses. It will start with basic programming topics using Python and cover using powerful Python packages such as Numpy, Scipy, Pandas, and Matplotlib that are essential for descriptive, predictive, and prescriptive analytics.

Terms offered: Spring 2017, Spring 2016, Spring 2015 Analysis of the capacity and efficiency of production systems. Development of analytical tools for improving efficiency, customer service, and profitability of production environments. Design and development of effective industrial production planning systems. Modelling principles are illustrated by reviewing actual large-scale planning systems successfully implemented for naval ship overhaul and for semiconductor manufacturing.Economics and Dynamics of Production: [+].

Prerequisites: 262A (may be taken concurrently), Mathematics 104 recommended.

Terms offered: Spring 2023, Fall 2022, Spring 2022 A course on financial concepts useful for engineers that will cover, among other topics, those of interest rates, present values, arbitrage, geometric Brownian motion, options pricing, portfolio optimization. The Black-Scholes option-pricing formula will be derived and studied. Stochastic simulation ideas will be introduced and used to obtain the risk-neutral geometric Brownian motion values for certain types of Asian, barrier, and lookback options. Portfolio optimization problems will be considered both from a mean-variance and from a utility function point of view. Methods for evaluating real options will be presented. The use of mathematical optimization models as a framework for analyzing financial engineering problems will be shown.Introduction to Financial Engineering: [+].

Terms offered: Spring 2023, Fall 2022, Spring 2022 Introductory graduate level course, focusing on applications of operations research techniques, e.g., probability, statistics, and optimization, to financial engineering. The course starts with a quick review of 221, including no-arbitrage theory, complete market, risk-neutral pricing, and hedging in discrete model, as well as basic probability and statistical tools. It then covers Brownian motion, martingales, and Ito calculus, and deals with risk-neutral pricing in continuous time models. Standard topics include Girsanov transformation, martingale representation theorem, Feyman-Kac formula, and American and exotic option pricings. Simulation techniques will be discussed at the end of the semester, and MATLAB (or C or S-Plus) will be used for computation.Financial Engineering Systems I: [+].

Prerequisites: 221 or equivalent 172 or Statistics 134 or a one-semester probability course.

Terms offered: Fall 2022, Fall 2021, Fall 2020 Advanced graduate course for Ph.D. students interested in pursuing a professional research career in financial engineering. The course will start with a quick review of 222: the basics of Brownian motion, martingales, Ito calculus, risk-neutral pricing in continuous time models. It then covers rigorously and in depth the most fundamental probability concepts for financial engineers, including stochastic integral, stochastic differential equations, and semi-martingales. The second half of the course will discuss the most recent topics in financial engineering, such as credit risk and analysis, risk measures and portfolio optimization, and liquidity risk and models.Financial Engineering Systems II: [+].

Terms offered: Spring 2019, Spring 2018 The course aims to train students in hands-on statistical, optimization, and data analytics for quantitative portfolio and risk management. In addition, the course will introduce elements of financial markets and asset classes. The emphasis will be on computational methods such as variants of GARCH, Black-Litterman, conic optimization, Monte Carlo simulation for risk and optimization, factor modeling. Students will undertake computational assignments and a group project. They will also manage hypothetical portfolios throughout the course.Portfolio and Risk Analytics: [+].

Terms offered: Prior to 2007 The course covers some convex optimization theory and algorithms, and describes various applications arising in engineering design, machine learning and statistics, finance, and operations research. The course includes laboratory assignments, which consist of hands-on experience.Introduction to Convex Optimization: [+].

Formerly known as: Electrical Engineering C227A Industrial Engin and Oper Research C227A.

Terms offered: Spring 2022, Spring 2021, Spring 2020, Spring 2019, Spring 2018, Spring 2017 Convex optimization as a systematic approximation tool for hard decision problems. Approximations of combinatorial optimization problems, of stochastic programming problems, of robust optimization problems (i.e., with optimization problems with unknown but bounded data), of optimal control problems. Quality estimates of the resulting approximation. Applications in robust engineering design, statistics, control, finance, data mining, operations research.Convex Optimization and Approximation: [+].

Terms offered: Spring 2023 This course is geared towards understanding operational, strategic, and tactical aspects of chain man agement. Topics covered are from a broad range that includes demand modeling, inventory management, facility location as well as process flexibility, contracting, and auctions. Important models

Research Areas+ Applied Electromagnetics RF Circuits Computer Vision Control Systems Embedded Systems ECE Education Research Integrated Circuits and VLSI MEMS and Microsystems Network, Communication and Information Systems Optics Photonics Plasma Science Engineering Power Energy Quantum Science Technology Robotics Signal Image Processing and Machine Learning Solid-State Devices Nanotechnology.

Events Distinguished Lectures Seminars Alumni Events Student Events PhD Defenses Cultural Diversity Events Other Events.

Chain Engineering Track (Ph.D.).

Industrial Engineering focuses on the design and analysis of manufacturing, distribution, and transportation systems. Students take fundamental coursework in optimization, stochastics, and statistics in order to build a firm base from which to deal with the myriad of issues that arise in settings involving modern chain systems modeling and analysis: production and inventory systems, vehicle routing and scheduling, warehousing, and logistics.

Several programs leading to master's and doctoral degrees are offered by the Department of Industrial and Systems Engineering. Each program has core requirements. Core requirements can be satisfied by previous coursework upon petition of the ISE curriculum committee. All core course prerequisites must also be satisfied. Prerequisites may be satisfied by (1) previous course work, (2) completing the prerequisite course without graduate credit, or (3) passing the final examination of the prerequisite course with a grade of B or better.

A Ph.D. student is required to complete core requirements with grades of B or better before being formally admitted to Ph.D. candidacy.

The minimum program for the master of science degree in Industrial and Systems Engineering consists of 24 credit hours of approved coursework and completion of a satisfactory thesis. Courses in other departments for which the student has the prerequisites may be integrated into this program. Subject to advisor approval, up to nine credit hours of 300 and 400-level courses from other departments may be included in the Industrial and Systems Engineering masters program. The other department courses usually include other engineering disciplines, mathematics, computer science, and business and economics.

This PhD in Industrial Engineering degree combines research with industry leaders and real world experience to prepare for a career in research, academic or business professions.

The Mechanical and Industrial Engineering graduate department offers a doctor of philosophy in Industrial Engineering. This advanced degree combines research with industry leaders and real world experience to prepare for a career in research, academic or business professions.

This PhD is awarded to students who demonstrate high academic achievement and research competence in the fields of mechanical or industrial engineering. To earn a PhD, a student must complete an approved, rigorous program of advanced course work and submit and defend an original dissertation of independent research. The mechanical and industrial engineering (MIE) department expects all successful doctoral candidates to show depth of knowledge and research innovation in their chosen field of specialization.

Can be combined with a Gordon Engineering Leadership certificate.

The ability to use basic engineering concepts flexibly in a variety of contexts.

Our graduates pursue careers within academia and beyond.

The Department offers a Ph.D. in Industrial Engineering for students with a background in engineering.

To maintain status as a graduate student, registration in each fall and spring semester is required. Otherwise, admission lapses and permission to re-enter must be granted.

Status until the degree has been granted. status is considered full time enrollment.

Upon completing the course requirements, passing the qualifying exams, and successfully defending the Ph.D. proposal, the student is eligible for admission to the Ph.D. candidacy.

There are no foreign language requirements for the Ph.D. degree.

Each application is assessed holistically. It is expected that an applicant receives a minimum score of 305 from GRE (verbal plus quantitative) and 3.50 GPA in their most recently earned academic degree. Other requirements are identical to the College of Engineering requirements. The transfer policy complies with the rules of the graduate school.

At least 50% of Courses at 700 level of IEN courses.

A written qualifying examination is to be taken by each doctoral degree candidate during the first year of graduate work. The department may specify that the student must take an oral examination as well. In those cases, normally, the student shall pass the written examination before the oral examination is conducted. Qualifying examinations normally will not be given during the summer months.

Additional courses up to 12 credits may be required for students who do not have any previous Industrial Engineering degree.

Assuming 12 graduate credit hours are approved to count toward the doctoral program.

The educational objectives of the Ph.D. program are to produce graduates who have:.

Built advanced technical knowledge in at least one specialty area of industrial engineering .

Gained advanced capability to apply advanced knowledge to engineering problems and.

Made significant contributions in at least one specialty area of industrial engineering.

Graduates will identify advanced engineering problems, search all possible methods for solution and implement the most appropriate one.

Graduates will demonstrate an ability to write effectively advanced engineering topics.

Graduates will have an ability to present their findings effectively advanced engineering topics.

Access to Students: Unique and expeditious connection to our students at all levels long before the normal recruiting phase (senior year (BS), MS and Ph.D. students).

Ability to influence the academic curriculum to better serve industry needs.

An opportunity to interact with comments and recommendations on internal department committee agendas (Facilities, Curriculum as two examples).

Interaction of industrial participants in CISE research projects.

Receiving guest lecturers from industry in courses and in the Colloquium Series.

Purdue School of Industrial Engineering continues to offer one of the nation preeminent PhD programs, providing research concentrations in human factors, manufacturing, operations research, and production systems. PhD students are encouraged to participate in multidisciplinary studies and multi-cultural educational efforts in one or of our diverse research areas, including:.

Our focus is to expand IE role in addressing 21st century challenges, expanding industrial frontiers, and designing and building the enterprise of the future.

We invite highly motivated individuals to join our program.