Research Experiences for Undergraduates (REU)
Applicants have been selected for REU 2022 at Haystack.
Applications for the summer of 2023 will be available starting in November 2022. Please come back then to appy!
Haystack Observatory invites all interested undergraduate students to apply for our paid summer research positions in science, engineering, and computer science. Our REU program has been held for decades, and we have seen many of our student interns go on to rewarding careers in STEM research.
The program extends from early June to mid August. People from groups under-represented in STEM fields are encouraged to apply. Undergraduate students eligible for this program must not have graduated prior to the start of the summer internship in June.
Support is provided by the National Science Foundation’s Research Experiences for Undergraduates program. The National Science Foundation, which sponsors this program, requires U.S. citizenship or permanent residency to qualify for positions supported under the REU Program. Undergraduate students eligible for this program must not have graduated prior to the start of the summer internship in June.
MIT is an equal opportunity/affirmative action employer.
REU 2022 projects (click titles for details)
Project 1: LEGO: Using dark clouds in the Milky Way to understand distant galaxies
It is hard to study fine details even in the most nearby galaxies. To give an example, some of the most exciting research today focuses on the formation of stars in the Milky Way and other galaxies. The star-forming sites in the Milky Way, also known as dark clouds, can be studied at an amazing level of detail. We can actually see how individual stars and planets form in our neighborhood. However, if we turn to galaxies, even the best telescopes available today cannot resolve dark clouds at a meaningful level of detail. Astronomers have therefore developed tricks to study the structure of clouds they cannot resolve. They study radiation from a variety of molecules, e.g. hoping that some molecules provide clues on dense gas while others might indicate that a dark cloud is being stirred up by embedded young stars. These are fascinating methods — but they have never been fully tested in the Milky Way. The LEGO survey therefore images dark clouds in the Milky Way to perform such tests. This teaches us lessons about star formation in the Milky Way and other galaxies. As part of this program, you will lead a small original research project that uses LEGO data. You will learn how to visualize and analyze the data from several astronomical observatories, and how to draw conclusions from the trends in the data. You will do this as a member in an international collaboration that includes researchers from the US, the EU, Chile, and Japan. Successful projects are expected to produce results that will be published as parts of the LEGO papers. Mentor: Jens Kauffmann.
Project 2: AERO-VISTA satellites
AERO-VISTA is a small satellite mission led by Haystack, scheduled for launch in 2022, which will test a novel “Vector Sensor” radio capable of sampling low radio frequencies from orbit in the Earth’s auroral zones. The satellite is currently being built, providing an excellent opportunity for students to get involved with a space mission at the ground floor and explore some of the capabilities of the sensor, the engineering of the satellite itself and/or aspects of planning for the mission. We envision a three-student team project working on different aspects of AERO technology and science. Possible projects could include (but are not limited to): mission planning software, capturing and analyzing signals using prototype AERO RF sampling instrument, and science software aimed at accelerating the discovery of new phenomena. Mentors: AERO-VISTA team.
Project 3: VLA observations of nearby stars
There are ~100 stars and brown dwarfs in our local galactic neighborhood (<5 pc). Many of those stars have exoplanetary systems, some already discovered and others still awaiting discovery. One emerging technique for discovering and characterizing exoplanets is the use of radio observations to search for magnetic interactions between stars and their planets. This project will focus on VLA P-band (230-470 MHz) observations of four nearby stars. The goal will be to reduce and image the interferometric data and then slice and dice it in time and frequency to search for radio emission from the star – or maybe from a planet! This project will provide experience using astronomical software such as CASA (python-based) and astropy as well as astronomical catalogs and associated tools. Mentor: Mary Knapp.
Project 4: Development of a seismic software package for Antarctic glaciology discovery
The student will further develop a software package to process seismic and geodetic data for Antarctic glaciology studies. The data will be collected by a novel seismogeodetic Ice Penetrator (SGIP) instrument and downloaded via satellite communications in near-real time after its expected Antarctic deployment in 2022. SGIP sensors include a broadband seismometer, a geodetic-quality GNSS receiver, and various meteorological and engineering parameters. In the course of this internship, the student will be trained with existing seismic data from Antarctica that are readily available and will learn how to process and manipulate the data using publicly available computer packages and/or python computer programs developed in-house. The data analysis includes, but is not limited to, handling miniSEED seismic data. The ultimate goal of the project is to build a python science package that process SGIP seismic data automatically, generating data products and visualization tools relevant to Antarctic cryospheric science. Mentors: Dhiman Mondal, Pedro Elosegui, John Barrett, Chester Ruszczyk.
Project 5: Sensing snow depth over Arctic sea ice using GPS reflectometry
Snow is a remarkable thermal insulator. As such, snow on top of sea ice has a very important role in the rate at which ice melts, and also grows in the Arctic Ocean. It is a critical climate variable. Unfortunately, it has always been a real challenge to know how much snow there is on Arctic sea ice. The new technique known as GPS reflectometry whereby GPS signals are reflected off the snow surface may offer the possibility of estimating snow depth. The student will use GPS data collected by a network of GPS ice-strain buoys (GIB) deployed on Arctic sea ice in February 2021 to explore this capability. The GIB instruments include a geodetic-quality GPS receiver. The dataset will include a number of collocated glaciological and atmospheric sensors. In the course of this internship, the student will learn to process geodetic data to analyze the multipath characteristics and to extract information about the snow depth in an automatic fashion using publicly available computer packages and/or self-developed computer programs using python. The data analysis includes, but is not limited to RINEX GPS data using . Results will be compared to satellite-based estimates such as NASA Icesat-2 and ESA Cryosat-2. The ultimate goal of the project is to build a science software package that can process GIB data automatically, generating data products and visualization tools relevant to Arctic cryospheric science, particularly time-varying snow depth. Mentors: Dhiman Mondal, Pedro Elosegui, John Barrett, Chester Ruszczyk.
Project 6: Observing black holes with the Event Horizon Telescope
The Event Horizon Telescope (EHT) [https://eventhorizontelescope.org/] is a planet-wide array of millimeter-wavelength radio telescopes that uses the technique of very long baseline interferometry (VLBI) to observe supermassive black holes. The goals of the EHT include testing general relativity and furthering our understanding of the astrophysics of accretion and outflow processes around black holes. The EHT is uniquely capable of resolving structures on angular scales of a few Schwarzschild radii around the black holes in the Galactic Center (Sgr A*) and the giant elliptical galaxy Virgo A (M87). The EHT has recently provided the first-ever images of a black hole [http://news.mit.edu/2019/mit-haystack-first-image-black-hole-0410] in M87, and EHT observations of Sgr A* and M87 in recent years have resolved their event horizon-scale structures. EHT data are also used to constrain the properties of the accretion flow and jets, to measure the black hole space-time described by its mass and spin, and to test Einstein’s general relativity. In this REU program, we will investigate a potential extension of the EHT to obtain further higher quality images of Sgr A* and M87. Mentors: Kazu Akiyama, Vincent Fish.
Project 7: The Great Haystack RFI Hunt
In this project we will investigate sources of RFI at MIT Haystack Observatory. We will collect data with our existing sensor systems and attempt to identify the primary sources of radio frequency interference. As part of the effort we will also use portable antennas and software radios to hunt down, localize, and record RFI signatures. These data will be used to create a catalog of interference sources for each of our astronomical and space science sensors. It will also lead to efforts to mitigate RFI when the interference discovered is under our direct control.
Spectrum coexistence is a major challenge facing radio science in the modern era. Scientific use of the radio spectrum aids in the study of Earth’s atmosphere, near space environment, and the larger astronomical universe. To enable fundamental research, scientific instruments span wide bandwidths and have high sensitivity. Proliferation of radio frequency (RF) systems pose new interference challenges. Historically, commercial, military and science users have been operating in relative spectral isolation and RFI issues have been addressed in an ad-hoc manner. However, signals used for radio science are often extremely weak and susceptible to interference. This has driven new radio science instruments to very remote locations. Most recently, the launch of satellite communications constellations is creating a new generation of globally visible mobile sources that cannot be easily avoided. Advanced approaches to the identification, classification, and mitigation of RFI are key to near term and future scientific applications of the radio spectrum.
The project will leverage software radio systems, portable antennas, and our larger instruments such as the Millstone Geospace Radar and Westford radio telescope. These will be used in combination with software in the Python and Julia programming languages to collect and analyze RFI data. It is most appropriate for a student with an interest in software radio systems, space science, or radio astronomy. Mentors: Frank Lind and Sharanya Srinivas.
Project 8: Measuring meteors and estimating winds with the Zephyr meteor radar network
Annual meteor showers are familiar to many from the increased frequency of visible “’shooting stars,’” but few people are aware that the Earth’s atmosphere is constantly being bombarded by dust-sized micro-meteoroids. These do not create visible meteors, but they are observable through radio scattering with a moderately-sized radar. Moreover, specular meteor trails provide a plentiful, natural tracer of upper-atmospheric winds through measurement of the line-of-sight Doppler shift of the reflected radio signal. Meteors occur sporadically in time and space, so they provide plentiful random samples of atmospheric wind and temperature that are hard to come by through any other means. Filling this gap in our observational knowledge is important for improving atmospheric models and studying coupling between the space environment, ionosphere, and atmosphere.
In collaboration with colleagues at the University of Colorado Boulder, we are building a meteor radar network called [Zephyr](https://www.haystack.mit.edu/geospace/geospace-projects/zephyr-meteor-radar-network/) to observe upper-atmospheric winds in the Rocky Mountain region. Zephyr has many tasks suitable for an REU student to make their own; the specific focus of this project will depend on the student’s skills and interests. Possible directions include:
• Optimization of the network geometry (transmitter and receiver locations) to improve wind field estimation
• Development of a dashboard for monitoring the meteor radar network, including live display of data, status, and operational control
• Improvement of the current Gaussian process regression wind estimation technique (a machine learning tool) using different mean/covariance functions or physics-based models
• Prototype testing of a local transmitter and receiver
• Analysis of meteor and wind data to inform future design decisions
We encourage students with an interest in any of these specific topics or a curiosity in geospace/atmospheric science or signal processing and estimation to apply! Mentor: Ryan Volz.
Project 9: GNSS measurements of space and terrestrial weather induced traveling ionospheric disturbances
GNSS satellites provide radio signals that can be sensed by ground recovers to measure ionospheric plasma density. The densely distributed GNSS receiver around the world , operated by many research and application communities, allow the space scientists to study 2-D ionospheric structures with unprecedented details both in time and space. A significant portion of the ionospheric dynamics arises from space weather and terrestrial weather disturbances under solar, geomagnetic, and meteorological influences. Traveling ionospheric disturbances (TIDs) are a ubiquitous and permanent feature of upper atmospheric variability and dynamics, and impose a primary challenge for accurate specification and prediction of the ionosphere and thermosphere state. We have been creating a very large GNSS TID database and made it possible to investigate space and terrestrial weather induced ionospheric variations. We are looking for a motived student to join us in exploring this database and analyzing TID characteristics. Computer language skills and proficiency, particularly with Python, are the essential requirement. Background in space, atmosphere, geophysics, or meteorology science is desired but not required. Mentors: Ercha Aa and Shunrong Zhang.
REU summer projects from past years are available in the presentation archives.
Please see the following sections for general information about the Haystack REU program. (Note that all information on this page is subject to change if necessary.)
Q: When can I apply for next summer? What is the time frame for applications?
A: Applications are made available on Thanksgiving each year for the following summer. The deadline is February 1; we notify successful applicants on March 1, followed by a series of notifications for acceptances if any are open after the first round of notifications. Please do not contact us about the status of your application. If you are not accepted, you will receive notification of this in March after all positions have been filled.
Q: My institution is on a quarterly system (or another schedule). This means that I won’t be available on the exact start date. Can I still apply?
A: Yes, please apply to the program. Make a note of your possible start date in your statement letter. The mentors will determine whether your earliest possible start date is acceptable within the requirements for their project. We prefer that people be available for the actual start date but realize that some institutions’ schedules make this difficult.
Q: Do you accept international students?
A: Unfortunately our sponsor, the NSF, requires applicants to be a U.S. citizen or permanent resident to qualify. We won’t be able to respond to inquiries regarding this.
Q: How is “undergraduate student” defined for this application?
A: An undergraduate student is a student who is enrolled in a degree program (part-time or full-time) leading to a baccalaureate or associate degree. Students who are transferring from one college or university to another and are enrolled at neither institution during the intervening summer may participate. High school graduates who have been accepted at an undergraduate institution but who have not yet started their undergraduate study are also eligible to participate. Students who have received their bachelor’s degrees and are no longer enrolled as undergraduates are not eligible to participate. Undergraduate students eligible for this program must not have graduated prior to the start of the summer internship in June.
Q: Will the REU program be held in person or online for 2022?
A: We hope that the Haystack internship program will be held in person in summer 2022. However, this decision is affected by local and MIT safety and health regulations. We continue to monitor the situation closely. (In 2020 and 2021, our research internship program was successfully held completely remote.) More to follow as information becomes available.
Q: Do you send notification letters when my application is submitted?
A: We will notify everyone of their application status after the final deadline for submission (February 1) has passed. If you are missing a piece of your application, we’ll let you know then.
Q: I applied but did not hear from you on March 1. How will I find out about my application’s status?
A: The first round of acceptances is sent out every year on March 1; if any of these positions is not accepted, it will be offered to the next round of candidates on March 8, and so on until all of the positions are filled. This means there is a series of acceptance letters, starting on March 1 and possibly continuing into March. We do not inform applicants of their status until all the positions have been accepted; if you are offered another position in the meantime, we suggest that you accept it, as we have only a very limited number of internships available.
The Haystack REU program starts in early June and ends mid-August. The 2022 REU program at Haystack will run from June 5, 2022, through August 12, 2022.
A uniform start date is preferred in order to conduct orientation activities for the group. For students on an academic quarter system or those interested in extending their stay, such requests can be considered on a case-by-case basis.
The Haystack summer undergraduate internship includes participation in the following:
- Science discussions: Haystack staff members lead discussions on numerous current research subjects, which include introductory information for all students, as well as a chance for active conversation with scientists, engineers, and other staff.
- Tours: Students will attend tours of the various Observatory facilities to learn about the extensive state-of-the-art instrumentation at Haystack.
- Group meetings: In addition to the frequent meetings between the sponsoring staff member and the student, several meetings with all students are held to review project status and encourage interactions among the students.
- Final reports and seminar: Students prepare brief final reports and create presentations on their projects to teach the Haystack community about their summer work.
- Attendance at conferences: Depending on available funds and meeting schedules, there are opportunities for students to participate in national conferences.
- Follow-up academic year program: Depending on available funds, interest, and project status, a student may continue the summer project during the following academic year.
- Travel support: Limited travel support is available for those students whose homes and colleges are more than 100 miles away from Haystack.
Students are assigned a mentor from the Haystack research staff for their summer work.
At the end of the summer, students present their research to a general audience at the Observatory. Their presentations are available in the REU presentation archives.
Compensation is provided as a weekly stipend of $600, paid biweekly.
The Observatory makes arrangements for student dormitory housing and pays the cost of housing for all students. Kitchen facilities are available in the dormitories. Daily transportation to and from Haystack is also provided.
(Students can arrange alternative housing on their own if they wish.)
The Observatory provides free daily transportation for all students from REU housing to our offices.
Accepted students must have a current medical insurance plan in place which will cover their health needs during the period of the REU program. Evidence of such insurance must be submitted upon acceptance, before the start of the program.