Assistant in Instruction (AI) Position Postings for Fall 2017
Note: Teaching assignments are dependent on course enrollments, candidate qualifications, and the availability of resources that must be approved by the Office of the Dean of the Faculty.
Should we be trying to live our lives so as to do the most good, and if so, what would that involve? Does a human embryo have a greater claim to protection than a chimpanzee? Should we be able to choose to end our own life, if we are terminally ill? Are we ethically required to limit our greenhouse gas emissions? What is an ethical diet? Are we justified in eating animals? Why should we act ethically, anyway? You will be encouraged to question your own ethical beliefs on these and other issues, and to explore the extent to which reason and argument can play a role in everyday ethical decision-making.
Instructor(s):Harrison Prather Frye; Peter Albert David Singer
If interested please contact: Name: Peter Singer E-mail: singerp@gmail.com Phone: 609-258-2739
Position 1 Primary Duties:
Number of AI Hours with Position: 1
Background Required: Applicants must have taken a course in ethics. Interested applicants should submit a CV, a letter detailing their knowledge of ethics and their teaching experience, and the names and email addresses of up to 3 professors who can testify to their teaching experience. Interested applicants should contact Professor Singer directly at singerp@gmail.com We will not make final commitments until we know the enrollment numbers for the course.
This course surveys the most important algorithms and data structures in use on computers today. Particular emphasis is given to algorithms for sorting, searching, and string processing. Fundamental algorithms in a number of other areas are covered as well, including geometric algorithms, graph algorithms, and some numerical algorithms. The course will concentrate on developing implementations, understanding their performance characteristics, and estimating their potential effectiveness in applications.
Instructor(s):Maia Ginsburg; Ananda Gunawardena; Kevin Wayne
If interested please contact: Name: Nicol Gotsis E-mail: ngotsis@cs.princeton.edu Phone:
Number of AI Hours with Position: 3
Background Required:
Starting and operating a complex venture in a regulated market is often faced with tremendous challenges in developing and validating the idea to attract investors and industry partners. With an initial perspective of what it takes to attract funding, the course will focus on teaching three main skills 1) What makes a complex business initially fundable through private and public resources, 2) Identifying the problem and validating the solution in a regulated, multi-stakeholder market 3) Launching the business and developing the operational plan post launch.
Instructor(s):Shahram Hejazi
If interested please contact: Name: Victoria Dorman E-mail: vdorman@princeton.edu Phone: 6092588676
Position 1 Primary Duties: assist in the classroom with managing in-class team exercises, manage communications with students, help with course materials review, help with grading
Number of AI Hours with Position: 3 AI hours
Background Required: interest in entrepreneurship
This hands-on course introduces students to analysis and actions required to launch and commercialize a tech company, through the use of Harvard Business School cases, visits from entrepreneurs, and two "field assignments". You will learn conceptual frameworks and analytical techniques for evaluating technologies, markets, and commercialization strategies. Additionally, you will learn how to attract and motivate the resources needed to start a company (e.g. people, corporate partners and venture capital), prepare business plans, structure relationships, refine product-market fit, and create and grow enterprise value.
Instructor(s):Christopher Brian Kuenne
Position 1 Primary Duties: help with course materials and managing in-class team exercises
A rigorous one-semester introduction to the organic chemical reactions of greatest biological importance, taught through the lens of metabolism. Covers organic mechanisms underlying fundamental enzyme-catalyzed reactions and quantitative analysis of enzyme kinetics and metabolic networks. For quantitatively-inclined students interested in biology, this course is an alternative to the standard two-semester organic chemistry sequence (CHM303/304). Does not replace CHM303/304 for Chemistry majors. Satisfies the organic chemistry requirement for Molecular Biology majors and provides appropriate preparation for subsequent studies in Biochemistry.
Instructor(s):Joshua D. Rabinowitz; Stanislav Yefimovic Shvartsman
If interested please contact: Name: Jennifer Brick E-mail: jbrick@princeton.edu Phone: 609-258-9407
Number of AI Hours with Position: 6
Background Required: please see course description. if you feel that you are a good fit, please contact us for a more detailed discussion. thank you!!
This course investigates language in its social, cultural, political, and historical contexts. Does your native language influence your perception, your behavior, and your culture? How does your identity influence properties of your language? What happens when unrelated languages come into contact for prolonged periods? How are new languages born? Why isn't English the official language of the United States, and should it be? We will explore these questions (and more) by engaging with the often contradictory opinions of specialists and the public, as well as with the empirical realities behind these different language situations.
Instructor(s):Laura Kalin
If interested please contact: Name: Yolanda Sullivan E-mail: syolanda@princeton.edu Phone: 609-258-8577
Position 1 Primary Duties: Linguistics is searching for an AI Grader to assist Prof. Laura Kalin in grading. AI will also be expected to attend lectures, hold office hours and interact with students. Teaching not required.
Number of AI Hours with Position: 2
Background Required: General background in Linguistics required.
This course provides an introduction to the burgeoning field of data science, which is primarily concerned with data-driven discovery and utilizing data as a research and technology development tool. We cover approaches and techniques for obtaining, organizing, exploring, and analyzing data, as well as creating tools based on data. Elements of statistics, machine learning, and statistical computing form the basis of the course content. We will focus on applications in the natural sciences.
Instructor(s):Yan Huang
If interested please contact: Name: Daisy (Yan) Huang E-mail: yanhuang@princeton.edu Phone: 609-258-9174
Position 1 Primary Duties: The Center for Statistics and Machine Learning at Princeton University has openings for AIs to teach precepts for SML 201 during the fall and spring of the 2017-2018 academic year. This course covers approaches and techniques for obtaining, organizing, exploring, and analyzing data, as well as creating tools based on data. In addition, it includes concepts such as random variables, sampling, probability distributions, estimations, hypothesis testing, and regressions, as well as relevant computational techniques. AIs are required to lead a precept (50-minute, TBD) and to attend two course lectures (either Tu/Th 11-12:20 or Tu/Th 3-4:20) each week. Other duties include: designing precept materials, writing up project and problem set solutions, grading, answering technical questions, weekly meeting with the course instructor, and holding regular office hours.
Number of AI Hours with Position: 2/precept
Background Required: Background in statistics is required; Proficiency in R is an asset
If interested please contact:
Number of AI Hours with Position: 3 or 6
Background Required: The main requirements are: knowledge of basic statistics is required, and a working knowledge of the programming language R is very desirable.