Would you like to get a head start on research and have the opportunity to explore various听interests as an听undergraduate?
The Your Own Undergraduate Research Experience听at听CU听program (YOU'RE听@听CU) is an exciting opportunity to gain practical research experience in engineering by linking undergraduate students with a graduate student mentor. Get hands-on experience as an听undergrad that听will inspire you to make a world of difference! You'll work on a research project 3鈥�5 hours per week and participate in a 15-week听seminar course on research practices.听You'll also develop your own research hypothesis and work through the research process,听culminating with a research paper and a poster session.听
Applicants must be engineering majors in good academic standing.
Details for Undergraduate Students
- Work with a graduate mentor for 3鈥�5 hours per week
- Gain exposure and learn the fundamentals of working in a lab environment, testing a hypothesis, and analyzing data
- Participate in a 15-week seminar course for one pass/fail credit
- Make a poster about your experience and present it with your graduate mentor at the end of the semester
Details for Graduate Student Mentors
- Work with an undergraduate student for 3鈥�5 hours per week
- Gain leadership and mentoring experience, attend a workshop on mentoring, and learn how to productively integrate an听undergraduate student into a lab environment. List this on your CV under teaching and mentoring experience!
- Gain an extra set of hands to help further your research
- Present a poster about the experience 鈥� created by your undergraduate mentee 鈥� at the end of the semester.
Projects for Spring 2024
Check your email for the program application.
Aerospace Engineering Sciences
Project Description
The overarching goal of this project is to support our work in identifying the origin of dust that impacts spacecraft and satellites. The student will work in CST Studio to model a spacecraft and dust impacts on it (no previous experience in CST is required). They will then work in MATLAB (or python) to interpret the collected results and compare it to known data from spacecraft missions and the IMPACT dust accelerator in order to gain additional details about the impact (velocity, mass, impact location, etc.). Through their research they will also learn about the dynamics of dust in the solar system and its sources.
Special requirements: Have some basic understanding of electrostatics
Desired majors: Aerospace Engineering Sciences, Applied Mathematics, Computer Science, Electrical Engineering, Electrical & Computer Engineering, Engineering Physics
Contact
Austin Smith, Graduate student
Zoltan Sternovsky, Faculty
Project Description
Imagine you could take a 3D scan of a component, click a few buttons, and get a graph showing the stress or flow field in or around the component. Or even better, the computer generates a new, optimized shape of the component.
We are close to realizing this vision. In Prof. Kurt Maute鈥檚 research group, we develop and use a software called MORIS for studying new methods in multi-physics analysis. This code lets us rapidly analyze complex geometry and create interesting engineering designs, but this requires flexible user input which makes interacting with some problems difficult. The goal of this project is to streamline the process for setting up and modifying inputs into MORIS with an improved user interface.
The primary contribution of the undergraduate student in this project is to implement a basic graphical user interface (GUI) that will create inputs for MORIS simulations. The student will use a coding language such as Python to develop the GUI, so an inclination for programming will suit them well for this project. Once this interface is created, the student will make use of their work to run some fundamental simulations using MORIS and visualize/analyze the results.
Special requirements: Completed introductory course involving programming, e.g. CSCI 1200, CSCI 1300, or ASEN 1320.
Desired majors: Aerospace Engineering Sciences,Applied Mathematics,Architectural Engineering,Biomedical Engineering,Chemical Engineering,Chemical & Biological Engineering,Civil Engineering,Computer Science,Creative Technology & Design,Electrical Engineering,Electrical & Computer Engineering,Engineering Physics,Environmental Engineering,Integrated Design Engineering,Mechanical Engineering
Contact
Adam Christopherson, Graduate student
Kurt Maute, Faculty
Project Description
This NSF-funded grant seeks support from a motivated undergraduate student to help with several aspects of our project. The grant is focused on human-autonomy teaming with an emphasis on understanding the longitudinal dynamics of trust in autonomous systems in operational environments.
A student on this project can assist with several aspects of the project in collaboration with the current PI and graduate student researchers. One need is conducting and analyzing qualitative interviews with users of autonomous systems to understand better how users trust autonomy. Another aspect of the grant that needs support is the development of a sorting task to recreate the operational demands seen in modern fulfillment warehouses. Finally, the grant also contains educational aims where portable math and science curriculums are being developed to share with rural Colorado high schools.
Project link:听Anderson lands prestigious NSF CAREER research award to study human-autonomy interactions
Desired majors: Aerospace Engineering Sciences,Applied Mathematics,Biomedical Engineering,Chemical & Biological Engineering,Computer Science,Creative Technology & Design,Electrical Engineering,Electrical & Computer Engineering,Engineering Physics,Integrated Design Engineering,Mechanical Engineering
Contact
Samuel Kurtin, Graduate student
Allison Anderson, Faculty
Chemical & Biological Engineering
Project Description
My work centers around the fungal luminescence pathway. Luminescence in mushrooms works similar to other examples of bioluminescence; with oxidation of a 鈥榣uciferin鈥� substrate resulting in an unstable oxygen intermediate that emits light when it breaks apart. I鈥檓 currently working on increasing the thermal stability of the luciferase protein in this genetically encodable pathway (the wild type starts to lose activity at temperatures higher than 22C). I鈥檓 really interested in plants and have a background in botany and biochemistry, so the overarching goal for this project is to make a tool that plant researchers can use to study plant behavior. I鈥檝e set up a tobacco system to eventually test this sensor in planta. I plan on further engineering this pathway by splitting the luciferase and hooking it up to the PYR-HAB system (mechanism for abscisic acid signaling pathway in plants) that others in my lab have worked with extensively to create in vitro sensors for small molecules other than abscisic acid.听
Special requirements:听Student must be able to work in 2 hour blocks for certain experiments.
Desired majors: Biomedical Engineering,Chemical Engineering,Chemical & Biological Engineering,听Environmental Engineering
Contact
Zo毛 Davis, Graduate student
Timothy Whitehead, Faculty
Project Description
This is a co-advised project that spans across two areas in biotechnological research to bring innovation to the cultivated (also known as lab-grown meat) space: Protein Engineering and Tissue Engineering. This is a good opportunity for a student that is interested in gaining some hands-on experience on how take care of bacteria, yeast, and/or mammalian cells for biotechnology research. The student will initially start out learning how to properly make growth medias and cell culture plates for each cell type and assist the graduate student in maintaining and taking care of such cell cultures. From there, the student will have the opportunity to learn how to utilize each cell type for engineering purposes, depending on student interest. In relation to bacteria and yeast, there is opportunity to learn how to transform genetic material into these organisms and learn techniques on how to analyze successful results. In relation to mammalian cells, there is opportunity to learn how to design experiments in relation to cell growth and how to quantitatively and qualitatively obtain and analyze cell culture results.
Special requirements:
- Student must have significant interest in working in the alternative protein space/working for a cellular agriculture company post-education (such as Upside Foods)
- Taken a course or course equivalent of basic cell biology
- Interested in learning how to take care of multiple cell types
- Have reliable transportation means to JSCBB East Campus
- Flexible hours and also be willing to occasionally go into lab at odd hours (outside of a 9-5)
Desired majors: Biomedical Engineering,Chemical Engineering,Chemical & Biological Engineering
Contact
Mia Keyser, Graduate student
Stephanie Bryant, Faculty
Project Description
This project uses organic materials to understand the fundaments of the chiral-induced spin selective effect, whereby electrons are filtered when transported through chiral materials based on their spin state. This phenomenon was experimentally verified in 1999 and has since become a burgeoning area of research. By studying the CISS effect we can apply spin polarization in a myriad of applications including increased reaction efficiency, advanced communication, spintronic devices, quantum computing, and other energy-related applications.听
As a student working on this project, your contribution will depend on the nature of what you are interested in and what skills you have to contribute. For instance, if you have taken O-chem and O-chem lab you may be able to help with synthesis; while if you don't have that background, you may contribute more to device/film fabrication. I work with organic materials to create aligned films to explore the CISS effect. In the near future, my efforts will be focused on material synthesis and characterization to determine the best uses for my materials. Eventually, I will be using these materials to create OLEDs, Spin valves, and photodetectors.
Special requirementss: Students should have some knowledge of chemistry (I.E. chem 1 and ideally also chem 2). The knowledge that a student brings to the table will determine the project scope they can work on. For instance, a student with several semesters of organic chemistry and organic chemistry lab will have the opportunity to work on synthesis. A student with more experience in general engineering courses may be better suited to material processing. I have no specific requirements other than someone who is motivated and interested in the project. Since this is such a new field of research, students should be willing to read literature and prepared to learn several unique techniques. This will require training for several weeks that students should be aware of when looking into this project.
Desired majors: Chemical Engineering,Chemical & Biological Engineering,Electrical Engineering,Engineering Physics
Contact
Noah Smith, Graduate student
Seth Marder, Faculty
Civil, Environmental & Architectural Engineering
Project Description
My PhD advisor and I are willing to collaborate with up to two undergraduate students through this program, to design and validate a set-up to measure the equivalent thermal resistance of an entire building envelope system using a test cell heated and cooled with a heat pump.
Special requirements: Hands-on experiences and willingness to work in the lab are preferred.
Desired majors: Aerospace Engineering Sciences,Applied Mathematics,Architectural Engineering,Biomedical Engineering,Chemical Engineering,Chemical & Biological Engineering,Civil Engineering,Computer Science,Creative Technology & Design,Electrical Engineering,Electrical & Computer Engineering,Engineering Physics,Environmental Engineering,Integrated Design Engineering,Mechanical Engineering
Contact
Mohammad Dabbagh, Graduate student
Moncef Krarti, Faculty
Project Description
UV technology is used during water treatment to disinfect pathogens and degrade micropollutants such as pharmaceuticals. As water scarcity increases, UV treatment will become increasingly necessary as UV can degrade and remove pollutants which elude conventional treatment. Conventional UV treatment uses lamps which emit at 254 nm, but a new technology called krypton chloride excimer (KrCl*) lamps which emit at 222 nm have emerged for water treatment applications. Very little is known about how molecules react under 222 nm light, so this research aims to fill that knowledge gap. Organic matter is present in all waters to be treated by UV. This organic matter is a complex mixture of micropollutants, biological matter, and natural molecules derived from plant matter. Organic matter affects nearly all water treatment processes by fouling membranes and acting as a precursor to toxic disinfection byproducts. This project will investigate the impact of 222 nm treatment on organic matter composition and character. More specifically, the student will spend their time on two main tasks: 1) running experiments using the UV apparatus to explore the influence of different variables (lamp intens).
Special requirements: To participate in lab work, the student must be able to have a 2-3 hour block free in their schedule.
Desired majors: Chemical Engineering,Chemical & Biological Engineering,Civil Engineering,Electrical & Computer Engineering,Environmental Engineering,Mechanical Engineering
Contact
Emma Payne, Graduate student
Karl Linden, Faculty
Project Description
The student will research the impact of urbanization on runoff and how nature-based solutions can be implemented to mitigate these effects. Additionally, the student will design and craft a didactic model to illustrate the studied effects, and the potential solutions, of runoff in urban environments. The final deliverable of this project will be a diorama-like model and a written script to communicate the research findings to the general public. Students interested in the intersection of engineering, science communication, and design are encouraged听to听apply.
Special requirements: Student must be available to work in SEEC (east campus).
Desired majors: Architectural Engineering,Civil Engineering,Environmental Engineering,Integrated Design Engineering
Contact
Santiago Ramirez Nunez, Graduate student
Aditi Bhaskar, Faculty
Computer Science
- Autonomous deployment of scale-model autonomous vehicles
- Using AI to recognize human activities in sensor data for health monitoring
- Genomic Compression Algorithm
- An interactive system for combining neural and symbolic representations for NLP
- Automatic segmentation of cardiac MRI data of CHD patient
Project Description
We have a robotic platform comprising a team of scale-model autonomous vehicles. These vehicles, known as AWS DeepRacer robots, are autonomous 1/18th scale cars. While these robots are constructed using a combination of hobbyist-grade components and customized equipment, they do not undergo extensive system identification processes. Our objective is to synthesize control software that adheres to specified temporal logic requirements. Consequently, we propose the following tasks:
- Interact with the robots to gather input-output data.
- Use the data to construct control barrier functions (CBFs) by solving convex programs for various scenarios.
- Develop custom software for the platform including a database of traffic scenarios, a reconfigurable road map, and elements such as traffic signs and obstacles. A graphical user interface (GUI) for the platform to adjust robot parameters, synthesize controllers for a subset of Linear Temporal Logic (LTL) properties using tools like pFaces or OmegaThreads (developed in our lab), simulate, and implement control actions on the robots.
Special requirements:
- Experience with C/C++
- Knowledge of systems and control is desired but not required
- Weekly meetings with the mentor
- Independent work
Project website:
Desired majors: Aerospace Engineering Sciences,Applied Mathematics,Architectural Engineering,Biomedical Engineering,Chemical Engineering,Chemical & Biological Engineering,Civil Engineering,Computer Science,Creative Technology & Design,Electrical Engineering,Electrical & Computer Engineering,Engineering Physics,Environmental Engineering,Integrated Design Engineering,Mechanical Engineering
Contact
Felipe Galarza Jimenez, Graduate student
Majid Zamani, Faculty
Project Description
This project focuses on adapting a graph-based neural network to the task of human activity recognition. This means recognizing the action of a human at each moment in time (e.g., brushing teeth, drinking water, walking, etc).
Now, the model will be trained and evaluated on datasets which contain 3 types of data collected from subjects: video data, depth sensor data, and motion sensor data. For example, a person performing the action "chopping a cucumber" will be captured by all 3 sensors. This project focuses on the question: "can we get the AI model to learn the relationships between the 3 data types in order to achieve high accuracy in recognizing activities"?
Your duties will depend on your technical expertise, but will likely consist of reading papers, learning deep learning principles, data preprocessing, running the model, analyzing results. You will work closely with Julia Romero, the PhD student leading this project in collaboration with AI researchers at Intel Labs.听
Keywords: AI, graph neural network, multimodal data fusion, activity recognition, smart home, Internet-of-Things, ubiquitous computing
Please email julia.romero@colorado.edu if you are interested!
Special requirements: We would love an undergraduate student who is capable of working independently and critical problem solving, and who is interested in graduate school.
Preferred qualifications:
- At least a Junior (or advanced Sophomore)
- Hands on experience/knowledge in data analysis, machine learning, deep learning
- Proficient/Capable in Python
- Interest in contributing to research and publishing听
- Highly motivated to learn and contribute to a difficult research project
There may be an opportunity for the student to continue research over the summer and the following year on this project.
There is flexibility so please contact julia.romero@colorado.edu if in doubt!
Desired majors: Aerospace Engineering Sciences,Applied Mathematics,Biomedical Engineering,Computer Science,Electrical Engineering,Electrical & Computer Engineering,Engineering Physics,Environmental Engineering
Contact
Julia Romero, Graduate student
Morteza Karimzadeh, Faculty
Project Description
My research focuses on designing algorithms and data structures for efficient search, storage, and computation over large-scale biomedical dataset (e.g. genome sequencing and genetic variant calling data).
For the spring semester I will be finishing up a compression project for a file format called 鈥淕WAS鈥� (Genome Wide Association Study). My goal is to write a compression algorithm for more efficient storage and data retrieval for this file. This will require running a lot of experiments on timing and storage used for different types of searches. The student鈥檚 responsibility will be to help design and run these experiments and report results in a meaningful way (data visualization). They will learn about biomedical data sets and what kinds of queries and questions we ask about them, and design experiments to test how our compression algorithm will help with those types of queries.
The student is welcome to help with development of compression work as well, but this level of work will not be required.
Special requirements: It would be helpful if the student has some familiarity with C++ and GitHub, but not required. No prior knowledge of biomedical datasets required, but if student has interest in biomedical research, added bonus!
Desired majors: Applied Mathematics,Biomedical Engineering,Computer Science,Electrical & Computer Engineering
Contact
Kristen Schneider, Graduate student
Ryan Layer, Faculty
Project Description
You've heard the buzz surrounding large-language-models (LLMs) such as ChatGPT and its cool capabilities- 听from being able to hold conversations with humans, to being able to perform tasks such as language translation and reading comprehension. 听However, LLMs have also been shown to have serious limitations - we can't understand their "reasoning process"; and have been shown to learn harmful stereotypes.
Our lab looks at combining LLMs with symbolic approaches like linear programming. We ask human experts in a field to define some rules, and then use LLMs to apply these rules to certain texts in order to make its predictions. This overcomes a lot of LLM limitations, and gives control to human users.听
We want to position these methods towards applications for the common good, so that social scientists can leverage such approaches to better understand problems like online hate speech.听
We would like researchers who can help us design an interface that implements neural-symbolic methods (NSM) so that it is accessible for non-tech folk. We need to 1) implement NSM for different tasks language context 2) build a web-interface that allows laypersons to utilize NSM for their research.
Special requirements: This is an applied research project. This means we require some proficiency in NLP/DL, as well as WebDev. You will have to explain how and why you are proficient in 1 of these areas (you took a class, learned through an internship, you built a project).听
Please don't feel discouraged if you feel you don't understand the math we use, we can work together to overcome gaps in learning!
Find technical requirements listed below:听
Must have proficiency:
- Python
- SVCs (Github)
- Writing clean, OO code
Choose One Proficiency:
- PyTorch/Tensorflow
- NLP libraries such as SpaCy
OR
- JavaScript framework of choice
- Knowledge of REST
Nice to have proficiency
- Docker
- CI/CD
- Writing tests
- Writing documentation
Candidate knowledge and experience, a plus:
Being able to talk about something you like (video game, hobby, movie, science fiction). You would be expected to commit the amount of time the program expects of you. We will meet weekly to discuss updates, but work will happen asynchronously.
Desired majors: Aerospace Engineering Sciences,Applied Mathematics,Architectural Engineering,Biomedical Engineering,Chemical Engineering,Chemical & Biological Engineering,Civil Engineering,Computer Science,Creative Technology & Design,Electrical Engineering,Electrical & Computer Engineering,Engineering Physics,Environmental Engineering,Integrated Design Engineering,Mechanical Engineering
Contact
Dananjay Srinivas, Graduate student
Maria Pacheco, Faculty
Project Description
Congenital heart disease (CHD) is the leading cause of birth defect related deaths, and affects approximately 1% of births in the U.S., about 25% of which is critical CHD where surgery or other interventions are necessary. The goal of this project is to develop an automated system that assists clinicians in understanding the condition of a CHD patient. Our system will input cardiac MRI data, automatically segment its different parts, i.e., left ventricle, left atrium, etc., and visualizes. In this way, the clinicians will not require to visually separate the heart parts manually for a huge number of patients.
The goal is very hard since heart of CHDs patient contains highly variable anatomical structure. It can involve a wide range of heart defects, e.g., shape changes within a chamber, abnormal connectivity between heart structures, abnormal structure locations, missing structures, etc. For this variability, it is hard for AI systems to find the latent anatomical pattern since test samples can be entirely different from training examples. Our plan is to continue to formulate this variability which can make an impact in the field of AI with child-cardiac image segmentation.
Special requirements: Students should have: (1) good python programming skills, and (2) basic knowledge on machine learning or deep learning.
Students will be expected to read research articles, give presentations, implement basic algorithms, collaborate with other researchers in the project, and, most importantly, assist in manual labeling of cardiac MRI data for training an AI model. Students may need to work 2 hours in a row.
Desired majors: Civil Engineering,Computer Science,Electrical Engineering,Electrical & Computer Engineering
Contact
Mohammad Imrul Jubair, Graduate student
Tom Yeh, Faculty
Electrical, Computer & Energy Engineering
Project Description
The student will extend the operating bandwidth of an existing (2-9.5 GHz) 3D printed conical spiral antenna. 3D printing by means of SLA with selective metallization will be used as a low-cost fabrication method when compared to conventional approaches. The antenna is ultimately intended to be part of a four-element array used in a reflector feed. Depending on the technical background and interest of the student, weekly tasking might include any/all of the following:
- Conducting design studies with commercial computational electromagnetic solvers.
- Assessing/designing for improved structural robustness and mitigation of vibrations.听
- Helping to manufacture and assemble the antenna (printing, post-processing, curing, soldering, etc).
- Characterizing the complex effective permittivity of 3D printed materials (low loss and lossy materials).
- Helping to measure the antenna using a vector network analyzer.
- Processing measured results (both impedance and far-field quantities).
- Design of the selectively plated support structure for monolithic array fabrication.
- Preparing a conference publication on research results.
Special requirements: Experience with CAD may be useful, though not required.
Desired majors: Aerospace Engineering Sciences,Applied Mathematics,Electrical Engineering,Electrical & Computer Engineering,Engineering Physics,Mechanical Engineering
Contact
Collin Wallish, Graduate student
Dejan Filipovic, Faculty
Materials Science and Engineering
Project Description
Polymers have recently been investigated for use in organic electronics such as organic electrochemical transistors (OECTs), organic photovoltaics (OPVs), and batteries due to their benefits over inorganic counterparts including flexibility, biocompatibility, and use as ultrathin films. In inorganic/metal electrode systems, the electrical double layer is clearly defined in a 2D space, however for a 鈥渟oft鈥� system, e.g. polymers, this presents as a much more complicated system due to absorption of electrolyte into the polymer.
In lab, I aim to understand polymer changes from a molecular to macro scale. An undergrad would be involved in the casting of films then using these films as electrodes for electrochemical charging with different electrolyte materials. They would then aid in the characterization of films using x-ray based instruments and python based analysis. Further involvement involves more independent characterization, in-situ methods, and synchotron based characterization.
Special requirements: Students should be available to work in blocks of at least 2 hours. Basic lab skills are necessary and an understanding of electrochemistry is useful but not required.
Project website:
Desired majors: Chemical Engineering,Chemical & Biological Engineering,Computer Science,Electrical Engineering,Electrical & Computer Engineering,Engineering Physics
Contact
Jonathan Thurston, Graduate student
Michael Toney, Faculty
Mechanical Engineering
Project Description
This project uses a human-centered research approach to design targeted, high-impact solutions to improve chemists鈥� wet lab research experience by increasing research efficiency, safety, and accessibility. Using both quantitative and qualitative research methods, we will aim to understand the needs of the chemist and the capabilities of commercially available robots to design human-robot collaborative systems in the chemical wet lab. The student will assist in the collection of data, and we will work together to code videos using ATLAS.ti and analyze data using Python and R Studio.
Special requirements: Experience in wet chemistry (at least one semester of a chemistry lab course taken for credit or research experience), and knowledge in basic statistics is desired. In addition, this project is very interdisciplinary so the student should be enthusiastic about learning about experimental organic chemistry, robotics, and new software.
Desired majors: Biomedical Engineering,Chemical Engineering,Chemical & Biological Engineering,Creative Technology & Design,Integrated Design Engineering,Mechanical Engineering
Contact
Diane Jung, Graduate student
Carson Bruns, Faculty
Project Description
In dynamic environments, we learn to modify our movements. These adjustments are related to learning and accommodating a new energetic landscape while reducing movement error. Learning changes in response to many factors, including reward and punishment and the reduction of error is accompanied by a reduction in metabolic cost. Does effort reinforce or impair learning? In this study, we will explore the effects of an effort cost that is dependent on movement error.
This project is an opportunity to work in human research at the intersection of engineering, neuroscience, and behavioral economics. As YOU'RE @ CU a research student on this project, you will help finalize the procedure for a robotic reaching study. Over the semester, you will support and then run your own data collections. Using your own data, you will visualize and quantify differences in reaching movements. Over the course of the semester, you will collaborate with your mentor to analyze data and develop a paper. You will also have the opportunity to attend a research conference. We will welcome you into the lab team and be introduced to ongoing projects in the Neuromechanics Lab.
Special requirements: Experience with MATLAB or Python is strongly preferred. Flexibility to work in 90 minute blocks in order to collect data is required. Great for students with an interest in psychology, human behavior and or human research.
Desires majors: Aerospace Engineering Sciences,Applied Mathematics,Architectural Engineering,Biomedical Engineering,Chemical Engineering,Chemical & Biological Engineering,Civil Engineering,Computer Science,Creative Technology & Design,Electrical Engineering,Electrical & Computer Engineering,Engineering Physics,Environmental Engineering,Integrated Design Engineering,Mechanical Engineering
Contact
Rachel Marbaker, Graduate student
Alaa Ahmed, Faculty
Project Description
This project aims to design and validate thin film composite (TFC) membranes, specifically shark-patterned and sinusoidal-patterned, that resist scaling using nanoimprint lithography. These membranes are ideal for concentrate management and industrial water desalination. They address challenges in methods like reverse osmosis (RO) and nanofiltration (NF) and thermal processes like membrane distillation (MD). They also could inhibit crystallization of salts on the membrane surface. We seek support for characterizing our membranes using atomic force microscopy. We aim to align with industry practices and to determine the concept's viability for industrial use.
Water demand is rising, necessitating the utilization of alternative sources like landfill leachate and brackish groundwater. However, these sources require desalination, resulting in a concentrated waste stream. This waste has significant eco-environmental implications, intensifying the need to reduce its volume and reclaim more potable water. Membrane patterning aims to reduce fouling and boost productivity.
Special requirements: This says that it's 3-5 hours a week. I would prefer if the work is done in 3-5 hour blocks one day a week in order to run experiments.
For coursework, it would be somewhat preferable if students have some kind of understanding of basic mass transfer. This is very much in the realm of chemical engineering, environmental engineering, and materials science, so students from those majors may be the most interested in this project.
Desired majors: Aerospace Engineering Sciences,Applied Mathematics,Architectural Engineering,Biomedical Engineering,Chemical Engineering,Chemical & Biological Engineering,Civil Engineering,Computer Science,Creative Technology & Design,Electrical Engineering,Electrical & Computer Engineering,Engineering Physics,Environmental Engineering,Integrated Design Engineering,Mechanical Engineering
Contact
Jacalyn Morgan, Graduate student
John Pellegrino, Faculty