GRADUATE ASSISTANTSHIPS: FUNDING OPPORTUNITIES

What is an Assistantship?
In engineering, a Graduate Assistantship (GA) is the most common way for students to fund their graduate studies. With a GA, the student is paid a stipend and perhaps tuition support in exchange for research or teaching assistant work. Research is normally done on the topic that is funded by an external agency or internally by Villanova, and on which the student will study to earn their MS or PhD. A teaching assistant might teach part of a lecture class or run problem sessions, hold office hours, organize and run a laboratory course, or grade for a professor. At some schools, the GA is labeled GRA if it applies to research. At Villanova, we use GA as the research assistantship and TA as the teaching assistantship. GAs are awarded based on the student’s interest in the research and their qualifications. TAs are awarded based on the student’s expertise and qualifications.

Eligibility
Awarding of all assistantships is handled by the academic departments and programs. There are no additional requirements beyond what the college or departments outline in their admissions criteria. Eligibility is limited to full-time students admitted for graduate degree programs; non-degree students (those students in the ICA program and not yet matriculated) and part-time students are not eligible. A GA must be enrolled in at least one course during the fall, spring, and summer semesters.

External Fellowships
A variety of fellowships funded by external organizations are also available (DOE, NSF, and SMART fellowships, private foundations, etc.). Information can be found at the websites of these organizations. Students should apply directly to the specific organization awarding a particular external fellowship.

Professional Development for PhD Students
If awarded a GA, in addition to stipend and tuition, the College of Engineering at Villanova has a unique professional development (PD) program for all PhD students. All full-time, post-qual PhD students are required to take at least one PD course. In addition, through additional courses and activities, a PhD student can earn a valuable certificate as a Teaching Scholar or an Industry Scholar. The certificate and PD courses are recorded on the student’s transcript and are highly valued by academia and industry in the job-search process. See further details here.

GRADUATE STUDENT OPEN POSITIONS
Updated 4/26/2024

GRADUATE ASSISTANTSHIPS IN CIVIL AND ENVIRONMENTAL ENGINEERING

Department: Civil and Environmental Engineering

Category: Graduate Assistantship

Student Classification: PhD

Discipline Area: Water Resources and Environmental Engineering

Project Title: Cross-Sectoral Water and Environmental Systems

Description: The project is in the area of water and environmental systems. Potential topics may include food-energy-water systems, microplastics and emerging contaminants in green stormwater infrastructure, and watershed systems analysis. The student and Dr. Good will determine a thesis topic together that may entail lab or field analysis and/or modeling. By joining the Good Research Group, the candidate will work within a team of other graduate students and undergraduate researchers and be involved with the Villanova Center for Resilient Water Systems.

Qualifications for Appointment: The candidate should have their BS or MS in Civil Engineering, Environmental Engineering, or related field (must be completed at the time of hire). Applicants should be self-motivated and curious, have excellent communication skills, and be willing to work in a collaborative environment. Experience with GIS, programming (Python, R, others), and/or laboratory work are valued and depend on the project but not required. Preference will be given to applicants who already have their M.S. in a relevant field. 

Start Date: Spring, Summer, Fall 2024

PIKelly GoodGoogle Scholar

LabGood Research Group

Department: Civil and Environmental Engineering

Position number: 22-BMW-1

Category: Graduate Assistantship

Student Classification: Master’s or PhD

Discipline Area: Water Resources

Project Title: Long-term Monitoring and Analysis of Green Stormwater Infrastructures

Description: The project is continuing a long history of monitoring a bio-infiltration rain garden and a constructed stormwater wetland. The project entails maintaining the monitoring program and analyzing associated data. Because of the long data record, the student and advisor will determine a thesis topic together that may entail additional lab or field analysis and/or modeling. The candidate will work within a team of other graduate students and undergraduate researchers on this stormwater research project and be involved with the Villanova Center for Resilient Water Systems.

Qualifications for Appointment: The candidate should have their BS or MS in Civil Engineering or related field (must be completed at the time of hire). The work will involve field and laboratory research which requires an ability and willingness to do physical work (potentially including entering manholes and the actual stormwater control measures). Additional work will include data analysis and potentially modeling.

Start Date: 06/01/2023

PI: Bridget Wadzuk; Google Scholar

Lab: Bridget Wadzuk faculty bio

GRADUATE ASSISTANTSHIPS IN ELECTRICAL AND COMPUTER ENGINEERING

Department: Electrical and Computer Engineering 

Category: Research Assistantship 

Student Classification: PhD 

Discipline Area: Radar Signal Processing and Comnmunication Systems 

Project Title: Integrated Sensing and Communications 

Description: The research project involves the applications of signal processing algorithms and machine learning methods in the area of integrated radar and communications 

Qualifications for Appointment: candidate should have a BSc and MSc in Electrical and Computer Engineering with high grades (GPA above 3.5) and have taken courses in signal processing, digital communications, and machine learning. Evidence and a list of prior publications should be provided. Having background in radar is preferred.  

Start Date: 09/1/2023 

PI: Moeness Amin
http://www35.homepage.villanova.edu/moeness.amin/

Lab:Radar Imaging Lab  

Department: Electrical and Computer Engineering 

Category: Research Assistantship 

Student Classification: PhD 

Discipline Area:  Signal Processing and Communications

Project Title: Interference-aware Constellation Design

Description: This research project will develop innovative signal transmission constellation for non-orthogonal multiple access (NOMA) channels using deep learning and signal processing techniques.

Qualifications for Appointment: The candidate should hold a BSc and MSc degree in Electrical and Computer Engineering or a related field. They should also possess a strong background in at least one of the following areas: signal processing, communications, or machine learning.

Start Date: Fall 2023 or Spring 2024 

PI:Mojtaba Vaezi

Lab:Wireless Networking Lab

GRADUATE ASSISTANTSHIPS IN MECHANICAL ENGINEERING

Department: Mechanical Engineering

Category: Graduate Assistantship

Student Classification: PhD

Discipline Area: Sustainability, Thermal Fluids Engineering

Project Title Data centers and Environmental Sustainability

Description: We are looking for a talented, motivated student to join our research center on Energy-Smart Electronic Systems (ES2) in Fall 2024, with a specific focus on predicting and mitigating the environmental burden associated with the data center industry.

Qualifications for Appointment: The student must have a Masters Degree in Mechanical Engineering with research experience in numerical or theoretical modeling, scientific publications (thesis and/or archival journal or conference publications), and a passion for promoting sustainability.

Start Date: 08/15/2024

PI: Aaron Wemhoff

LabCenter for Energy-Smart Electronic Systems (ES2): Center for Energy Smart Electronic Systems (ES2)

Department: Mechanical Engineering

Category: Graduate Assistantship

Student Classification: PhD

Discipline Area: Mechanics of Materials, Machine Learning

Project Title: First-principles calculations of advanced structural materials for fusion energy applications

Description: The student will work closely with Dr. David Cereceda to conduct first-principles density functional theory calculations of structural materials exposed to extreme environments. Qualifications for Appointment: The ideal candidate is expected to have a solid background in solid-state density-functional theory computations, machine learning and Python programming. To apply, please send a cover letter outlining your qualifications, research experience and interests, CV, and a list of three references to Dr. David Cereceda. The evaluation process will start immediately and will continue until the position is filled.

Start Date: 01/15/2023

PI: David Cereceda

LabMultiscale Modeling of Materials and Machine Learning Laboratory (M4L Lab): https://www.m4l-lab.com/

Department: Mechanical Engineering

Category: Graduate Assistantship

Student Classification: PhD

Discipline Area: Mechanics of Materials, Machine Learning

Project Title: Physics-informed machine learning models of bio-inspired materials

Description: The student will work closely with Dr. David Cereceda to design bio-inspired structural materials with superior properties.

Qualifications for Appointment: The ideal candidate is expected to have a solid background in computational mechanics, FEM modeling, machine learning and Python programming. To apply, please send a cover letter outlining your qualifications, research experience and interests, CV, and a list of three references to Dr. David Cereceda. The evaluation process will start immediately and will continue until the position is filled.

Start Date: 01/15/2023

PI: David Cereceda

LabMultiscale Modeling of Materials and Machine Learning Laboratory (M4L Lab): https://www.m4l-lab.com/

Department: Mechanical Engineering

Position number: 21-CL-2

Category: Graduate Assistantship

Student Classification: PhD

Discipline Area: Thermal Fluids

Project Title: Computational Investigation of Odor-Guided Flapping Flight in Nature

Description: This project aims to develop a multi-physics computational framework to investigate the underlying flow physics of odor tracking flight in nature. This framework will integrate several challenging computational components, including odor transport in turbulent flow, flow-structure-interaction, and reinforcement learning for POMDPs.

Qualifications for Appointment: A solid background in numerical methods for PDEs, strong hands-on experience with programming in Fortran or C++, and effective communication skills (written/spoken English) are required. Previous in-house code development experience is strongly preferred.

Start Date: 01/15/2023

PI: Chengyu Li, Google Scholar

Lab: Flow Simulation & Flow Physics Lab

Above are the currently available GA openings in the College of Engineering. Please contact the PI if interested. Students are also encouraged to contact faculty members to explore other opportunities for research and possible GA funding, TA work, and scholarships. Several specific qualifications for appointment are provided below. Others appear under Guidelines and Responsibilities for Graduate Students. Please review all qualifications for appointment before contacting a faculty member.