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Qualcomm Fellow-Mentor-Advisor (FMA) Fellowships

The Qualcomm Fellow-Mentor-Advisor Fellowship is a fellowship program for outstanding UCSD Jacobs School of Engineering doctoral students nominated by their Faculty Advisors.

Up to 4 FMA fellowships will be awarded this year.

The Program brings together teams which include an engineering Ph.D. candidate, his/her faculty advisor and an engineering mentor from Qualcomm. The goal is to foster in-depth connections between the Jacobs School faculty and Qualcomm engineers while enhancing the education of doctoral students.

Forms and Deadlines

Interest Statement March 5, 2018
Notification for Full Proposal April 20, 2018
Final Proposal Due June 4, 2018
Award Notification August 2018

Provisions of the Award

Fellowship Includes:

  • Student's tuition, fees and stipend for up to 12 months.
  • Discretionary funding to the Faculty Advisor's research program related to the research plan of the fellow, including funding for conference travel for fellow.
  • Total monetary value of the award is: $75,000.
  • Fellows will receive guidance from experienced Qualcomm Mentor.
  • Payment of the fellowship award, as described above, will be made directly to the university, and is not transferable to another academic institution or department.

Eligibility Criteria

  • Applicants for the Qualcomm FMA must be nominated by their faculty advisor.
  • Student must be enrolled as a doctoral student in good standing within one of the six academic departments of the UCSD Jacobs School of Engineering.
  • Students must have completed at least one year of study at UCSD in their doctoral program.
  • Student should be working in a research topic of interest to Qualcomm's future business development.
  • Final applications must have a Qualcomm Mentor identified (please see below).

Technical Areas of Interest

Qualcomm has provided some technical areas of interest. Other technical area proposals not indicated below can be submitted, as this list is not all inclusive.

Advanced Semiconductor Electronics:
  • Ultra-low (uW) power embedded platform for edge computing (ULP architectures and designs, HW accelerators, power generation and management, novel memories, security)
  • Novel materials and heterogeneous integration (2D semiconductors, GaAs, GaN, etc.)
  • CMOS (3D IC, thermal-aware designs, circuits, advanced packaging techniques, etc.)
  • RF / analog ASICs and architectures (Sub-6GHz 5G power amplifiers, mmWave RFIC for 5G NR, adaptive RF signal processing algorithms, etc.)
  • Advanced antenna (millimeter-wave and phase-array antennas), novel antenna materials, structures and implementations
  Processor Architecture and Implementation:
  • Novel processor architectures, microarchitectures, extensions, and accelerators
  • Multimedia and gaming architectures (not limited to GPU, GPGPU, VLIW, DSP, etc.)
  • Novel architectures for artificial intelligence, edge training and inference
  • Security features of CPUs and accelerators at the instruction set, memory system, and SOC levels
Autonomous Driving:
  • Advanced sensors and sensor fusion
  • Imaging radar
  • Deep learning with guarantees
  • Safe and reliable path planning
Machine Learning:
  • Natural language processing
  • Computer vision
  • Reinforcement and continual learning
  • On-device training
  • Intermediate representation for machine learning workloads/compilers
Advances in Communication Techniques and Theory:
  • Ultra-reliable and low latency communications
  • Wide-area wireless networks using high-frequency and mmWave spectrum
  • Massive MIMO, network MIMO, and coordinated multipoint processing
  • Wireless systems for unlicensed/shared spectrum
  • Low energy networks (Bluetooth LE, 802.15.4, Zigbee, Wi-Fi, etc.)

Identifying a Qualcomm Mentor

  • Qualcomm Mentors are Qualcomm employees whose expertise is appropriate to the research project and who will be an integral member of the research team.
  • Qualcomm Mentors may be individuals with whom the Faculty Advisor already works.
  • In the case that a mentor is unknown, please indicate on Interest Statement. Qualcomm will circulate the Interest Statement to see if there is an appropriate engineering leader at Qualcomm who may want to serve as a mentor on the project.
  • If a mentor is identified, the Qualcomm Mentor will contact the Faculty Advisor so they can confirm mutual interests and possibly invite the faculty member to present a seminar at Qualcomm before the final application is submitted.

How to Apply

Step One: Interest Statement

Submit interest statement including a one-paragraph description of proposed student research project, and indication of whether a Qualcomm Mentor is identified or not.

Step Two: Application

  • Student's research project description (1-2 page), should be developed in consultation with Qualcomm Mentor.
  • Student Nominee's CV
  • Faculty Advisor's short CV (1-2 page)

Interest Statement and Applications should be submitted by the Faculty Advisor.

Selection Process

The Jacobs School will review applications to ensure they meet eligibility requirements for program. Qualcomm will review applications and make final award selections.


Inquiries

Lisa Russon
(858) 534-4950
lrusson@ucsd.edu

Jan Dehesh
(858) 534-2329
jdehesh@ucsd.edu

2017-18 FMA Winners

Faculty Advisor: Ian Galton
Student Fellow: Raghavendra Haresamudram
Qualcomm Mentor: Prasad Gudem
Project Title: Adaptive Digital Linearization of Handset Receivers to Maximize Data Throughput
Faculty Advisor: Drew Hall
Student Fellow: Xiahan Zhou
Qualcomm Mentor: Seung Kang
Project Title: Ultrasensitive CMOS MTJ Sensors:Advances towards Lifescience, Automotive, and AR/VR
Faculty Advisor: Andrew Kahng
Student Fellow: Ahmed Youssef
Qualcomm Mentor: Kambiz Samadi, David Kidd
Project Title: 3DV PDN Pathfinding and Optimization Methods
Faculty Advisor: Gabriel Rebeiz
Student Fellow: Bhaskara Rupakula, ECE
Qualcomm Mentor: Allen Tran
Project Title: Advanced Automotive Radars

View All Past Winners