Office of the Dean of the Graduate School

Computer Science

COS 126 — Computer Science: An Interdisciplinary Approach

An introduction to computer science in the context of scientific, engineering, and commercial applications. The course will teach basic principles and practical issues, and will prepare students to use computers effectively for applications in computer science, physics, biology, chemistry, engineering, and other disciplines. Topics include: hardware and software systems; programming in Java; algorithms and data structures; fundamental principles of computation; and scientific computing, including simulation, optimization, and data analysis. No prior programming experience required. Lectures, with labs and precepts.

Instructor(s):Adam Finkelstein; Alan Kaplan; Jérémie Lumbroso; Soohyun Nam Liao

If interested please contact:
Name: Nicki Mahler
E-mail: ngotsis@cs.princeton.edu
Phone: 609-258- 5387

Position 1 Primary Duties:

Number of AI Hours with Position:

Background Required:

East Asian Studies

EAS 231 — Chinese Martial Arts Classics: Fiction, Film, Fact

This course provides an overview of Chinese martial arts fiction and film from earliest times to the present day. The focus will be on the close-reading of literary, art-historical, and cinematic texts, but will also include discussion of the significance of these works against their broader historical and social background. Topics to be discussed: the literary/cinematic pleasure of watching violence, the relationship between violence and the law, gender ambiguity and the woman warrior, the imperial and (trans)national order of martial arts cinema, and the moral and physical economy of vengeance.

Instructor(s):Paize Keulemans

If interested please contact:
Name: Professor Paize Keulemans
E-mail: pkeulema@princeton.edu
Phone: 646-458-1167

Position 1 Primary Duties:
Teach one or two sections of EAS 231: Chinese Martial Arts Classics. The course covers famous literary and cinematic texts from the Han dynasty to the Xi Jinping era, including Sima Qian%u2019s %u201CBiographies of the Assassins,%u201D Zhang Yimou%u2019s %u201CHero,%u201D and the late-Ming classic %u201COutlaws of the Marsh.

Number of AI Hours with Position: 1-2

Background Required:

ENE 202 — Designing Sustainable Systems: Understanding our environment with the Internet of Things

The course presents anthropogenic global changes and their impact on sustainable design. The course focuses on understanding the underlying principles from natural and applied sciences, and how new basic Internet of Things digital technology enables alternative system analysis and design. Material is presented in 2 parts: 1) Global Change and Environmental Impacts: studying our influences on basic natural systems and cycles and how we can evaluate them, and 2) Designing Sustainable Systems: synthesizing the environmental science with new IoT in an applied design project.

Instructor(s):Forrest Michael Meggers

If interested please contact:
Name: Forrest Meggers
E-mail: fmeggers@princeton.edu
Phone:

Position 1 Primary Duties:
Responsibilities will include leading lab sessions, attending lectures, grading, holding office hours. The labs and final project will involve helping develop and support Internet of Things hardware and software setup and management.

Number of AI Hours with Position: 3-6

Background Required:
Ideally, candidate will have good computer programming and computer hardware skills. The primary platform used is the Particle.io hardware and online IDE programming (similar to C or Arduino), and wetting up REST API and Webhook connections. All candidates must have completed the AI Orientation offered by the McGraw Center for Teaching and Learning by the time classes begin.

Program in Environmental Studies

ENV 354 — Climate and Weather: Order in the Chaos

This course focuses on the relationship between climate and weather events: each weather event is unique and not predictable more than a few days in advance, large-scale factors constrain the statistics of weather events, those statistics are climate. Various climatic aspects will be explored, such as the geographic constraints, energy and water cycling, and oceanic and atmospheric circulation, solar heating, the El Niño phenomenon, ice ages, and greenhouse gases. These climate features will be used to interpret the statistics of a number of weather events, including heat waves, tropical cyclones (hurricanes and typhoons) and floods.

Instructor(s):Gabriel Andres Vecchi

If interested please contact:
Name: Amber Lee
E-mail: amberlee@princeton.edu
Phone: 6092584998

Position 1 Primary Duties:

Number of AI Hours with Position: Upto 6.0

Background Required:

Molecular Biology

MOL 250 — Food, Drugs and Society

The current environment in the US for the use and abuse of foods and drugs will be examined from a scientific fact-based perspective. Historical, economic, marketing, political, and public health drivers will be considered. Specific topics include government dietary recommendations (food politics), dietary supplements (from Vitamins to herbal extracts), pharmacology and ethical drug development (sulfa drugs, NSAIDS, etc), addiction and substance abuse (alcohol, nicotine, stimulants, opioids, etc), Alzheimer's disease and the problem of long-term care in an aging population, and Psychedelic drug use and abuse (psilocybin, mescaline, LSD, etc).

Instructor(s):Jeffry Benton Stock

If interested please contact:
Name: Jeff Stock
E-mail: jstock@princeton.edu
Phone: 6092586111

Position 1 Primary Duties:
One precept per week, attend lecture, grading. Same TA can lead up to three precepts.

Number of AI Hours with Position: 2

Background Required:
Background requested (but not required): An interest in public policy, healthcare, political science, psychopharmacology, and the law.

MSE 201 — Materiality of Design

An introduction to the influence of materials in artistic, architectural, and product design. Primarily focused on the artist, architect, and designer who want to know more about materials and the principles of materials science and characterization. This class is also for the engineer who wants to study more about design. Focus will be on how technical properties, aesthetics, sustainability, manufacturability, and ergonomics relate to material properties and selection.

Instructor(s):James S. Smith

If interested please contact:
Name: Jim Smith
E-mail: jss10@princeton.edu
Phone: 6092588977

Position 1 Primary Duties:
Grading, research.

Number of AI Hours with Position: 3

Background Required:

Politics

POL 362 — Chinese Politics

This course provides an overview of China's political system. We will begin with a brief historical overview of China's political development from 1949 to the present. The remainder of the course will examine the key challenges facing the current generation of CCP leadership, focusing on prospects for democratization and political reform. Among other topics, we will examine: factionalism and political purges; corruption; avenues for political participation; village elections; public opinion; protest movements and dissidents; co-optation of the business class; and media and internet control.

Instructor(s):Rory Truex

If interested please contact:
Name: Amanda Kastern
E-mail: akastern@princeton.edu
Phone: 609-258-4766

Position 1 Primary Duties:
AIs needed to attend virtual lectures, teach precept sections and grade student work.

Number of AI Hours with Position: 2-6

Background Required:
Knowledge of the subject matter (Chinese politics).

Politics

POL 210 — Political Theory

This course will introduce students to major topics in political theory, such as the nature of justice, the relationship between individual liberty and the state, the boundaries of the political community, democracy and representation, and the ethics of resistance and revolution. The course will explore these issues through immersive historical simulations. Students will first learn about major ideas and debates in political thought and then apply what they have learned by playing the roles of important actors during pivotal events in history, such as wars, revolutions, and struggles for power and liberation.

Instructor(s):Javier S. Hidalgo

If interested please contact:
Name: Amanda Kastern
E-mail: akastern@princeton.edu
Phone: 609-258-4766

Position 1 Primary Duties:
AIs needed to attend virtual lectures, teach precept sections and grade student work.

Number of AI Hours with Position: 2-6

Background Required:
Knowledge of the subject matter (political theory).

Politics

POL 345 — Introduction to Quantitative Social Science

Would universal health insurance improve the health of the poor? Do patterns of arrests in US cities show evidence of racial profiling? What accounts for who votes and their choice of candidates? This course will teach students how to address these and other social science questions by analyzing quantitative data. The course introduces basic principles of statistical inference and programming skills for data analysis. The goal is to provide students with the foundation necessary to analyze data in their own research and to become critical consumers of statistical claims made in the news media, in policy reports, and in academic research.

Instructor(s):Gleason Judd

If interested please contact:
Name: Amanda Kastern
E-mail: akastern@princeton.edu
Phone: 609-258-4766

Position 1 Primary Duties:
AIs needed to attend virtual lectures, teach precept sections and grade student work.

Number of AI Hours with Position: 2-6

Background Required:
Knowledge of the subject matter (statistics/quantitative methods).

Politics

POL 240 — International Relations

Why do some countries fight wars while others are peaceful? Are nuclear weapons a source of stability or instability? What explains the current trade war with China? This course will provide a theoretical framework to help students better answer these questions, as well as other questions central to the study of international conflict and cooperation. Broad topics will include the causes of war and peace, the sources of transnational terrorism, the logic behind modern-day trade wars, the politics of international monetary policy, the systemic challenges to combating global warming, and the promise and peril of foreign aid.

Instructor(s):Rebecca Louise Perlman

If interested please contact:
Name: Amanda Kastern
E-mail: akastern@princeton.edu
Phone: 609-258-4766

Position 1 Primary Duties:
AIs needed to attend virtual lectures, teach precept sections and grade student work.

Number of AI Hours with Position: 2-6

Background Required:
Knowledge of the subject matter (international relations).

Religion

REL 251 — Christianity in the Roman Empire: Secret Rituals, Mystery Cults, and Apocalyptic Prophets

How did Jesus' earliest followers interpret his life and death? What were secret initiation rites and love feast gatherings about? How did women participate in leadership? How did the Roman government react to this movement and why did Jesus' followers suffer martyrdom? How did early Christians think about the end of the world, and what did they do when it did not happen? This course is an introduction to the Jesus movement in the context of the Roman Empire and early Judaism. We examine texts in the New Testament (the Christian Bible) and other relevant sources, such as lost gospels, Dead Sea scrolls, and aspects of material culture.

Instructor(s):Matthew Larsen

If interested please contact:
Name: Kerry Smith
E-mail: kerrys@princeton.edu
Phone:

Position 1 Primary Duties:
Attend weekly lectures held Mondays/Wednesdays 11:00am - 11:50am, one to two 50-minute precept(s) per week, meetings with the instructor, holding virtual office hours, and assessing student papers/grading.

Number of AI Hours with Position: 1-2 AI hours depending on enrollments.

Background Required:
Background and/or interest in the academic study of Religion is preferred. If interested please send CV to kerrys@princeton.edu.

Center for Statistics and Machine Learning

SML 201 — Introduction to Data Science

Introduction to Data Science provides a practical introduction to the burgeoning field of data science. The course introduces students to the essential tools for conducting data-driven research, including the fundamentals of programming techniques and the essentials of statistics. Students will work with real-world datasets from various domains; write computer code to manipulate, explore, and analyze data; use basic techniques from statistics and machine learning to analyze data; learn to draw conclusions using sound statistical reasoning; and produce scientific reports. No prior knowledge of programming or statistics is required.

Instructor(s):Daisy Yan Huang

If interested please contact:
Name: Daisy Huang
E-mail: daisyhuang@princeton.edu
Phone:

Position 1 Primary Duties:
The Center for Statistics and Machine Learning at Princeton University has openings for AIs to teach precepts for SML 201: Introduction to Data Science during the Spring 2021 semester. The course covers approaches and techniques for obtaining, organizing, exploring, and analyzing data. The material covered also includes predictive modeling, R programming for data science, and the basics of statistical inference (random variables, sampling, probability distributions, parameter estimation, hypothesis testing, and linear regression.) We teach introductory programming with an approach inspired by functional CS1 courses, and emphasize simulation-based inference in our pedagogy. AIs are required to lead an 80-minute precept and to attend two course lectures (either Tu/Th 11-12:20 or Tu/Th 3-4:20) each week. AIs will also grade written student work. Interested candidates should contact Daisy Huang with a resume/CV and their undergraduate and graduate transcripts as soon as possible. Please copy Susan Johansen on the email. Applications are accepted until all positions are filled.

Number of AI Hours with Position: 3 per precept

Background Required:
Background in statistics and programming. Enthusiasm for teaching beginners. Proficiency in R is an asset. We welcome applications from students in both technical disciplines and the candidates working with data in the social sciences.

Center for Statistics and Machine Learning

SML 310 — Research Projects in Data Science

A project-based seminar course in which students work individually or in small teams to tackle data science and machine learning problems, working with real-world datasets. The course emphasizes critical thinking about experiments and large dataset analysis and the ability to clearly communicate one's research. This course is intended to support students in developing the analytical skills necessary for quantitative independent work; students should consult with their home department about how this course could appropriately complement, but not replace, their independent work requirements.

Instructor(s):N/A

If interested please contact:
Name: Daisy Huang
E-mail: daisyhuang@princeton.edu
Phone:

Position 1 Primary Duties:
The Center for Statistics and Machine Learning at Princeton University has openings for an AI to participate in delivering SML310 -- Research Projects in Data Science in the Spring 2020 semester. Students in SML 310 will work on a substantial independent project in data science. Lecture topics will support student projects and will include supervised and unsupervised machine learning methods, deep learning, data visualization, and hierarchical modeling. The AI will work with students who are working on projects that fall within the AI's specialization, hold office hours, assist with grading, hold Python workshops for students who are beginners in Python, and lead some of the precept sessions. Interested candidates should contact Daisy Huang and Jonathan Hanke. Please attach a resume/CV and both undergraduate and graduate unofficial transcripts. Applications will be considered on an ongoing basis.

Number of AI Hours with Position:

Background Required:
experience with and enthusiasm for machine learning and data science; expertise in data analysis using Python and/or R. Experience with TensorFlow, PyTorch and/or Stan would be an asset but is not a requirement. We encourage applications from candidates in core data science disciplines as well as any other candidates whose work involves advanced quantitative analysis.

Princeton School of Public and International Affairs

SPI 345 — Prejudice: Its Causes, Consequences, and Cures

Prejudice is one of the most contentious topics in modern American society. There is debate regarding its causes, pervasiveness, and impact. This goal of this course is to familiarize students with the psychological research relevant to these questions. We will review theoretical perspectives on prejudice to develop an understanding of its cognitive, affective, and motivational underpinnings. We will also discuss how these psychological biases relate to evaluations of, and behavior toward, members of targeted groups. In addition, research-based strategies for reducing prejudice will be discussed.

Instructor(s):Stacey A. Sinclair

If interested please contact:
Name: Jan Burch
E-mail: jburch@princeton.edu
Phone: 609-258-4817

Position 1 Primary Duties:
Attend Lectures M/W, 11:00-11:50 AM. Lead 3 precept sections.

Number of AI Hours with Position: 3

Background Required: