[4eyes] FW: [FACULTY] Qualcomm Innovation Fellowship Opportunity for Ph.D. students - Information Session Tuesday, Oct. 23rd, 3pm, MRL 2053

[Matthew Turk]

Four Eyes Lab PhD students,

 

Please note Benji’s email below about the Qualcomm Innovation Fellowship and the information session on Tuesday. The opportunity is for a $100k fellowship for a team of two PhD students. The research areas of interest are listed below.

 

Read through the materials, think about possibilities of teaming with another PhD student for a proposed project, and consider attending the information session at 3pm on Tuesday (in MRL 2053).

 

                Matthew 

 

From: faculty [mailto:faculty-bounces at lists.cs.ucsb.edu] On Behalf Of benji
Sent: Thursday, October 19, 2017 11:21 AM
To: grads at lists.cs.ucsb.edu; faculty at lists.cs.ucsb.edu
Subject: [FACULTY] Qualcomm Innovation Fellowship Opportunity for Ph.D. students - Information Session Tuesday, Oct. 23rd, 3pm, MRL 2053

 

 

 

**Please distribute to all faculty and graduate students in your departments** 

 

Chad Sweet, from Qualcomm Research, will be on campus Tuesday October 23rd at 3pm in MRL 2053 to provide information on the Qualcomm Innovation Fellowship. There are many areas which align with our research at UCSB, see below. Please have faculty and grad students attend. 

 

Information: 

 

It is our pleasure to announce the launch of the Qualcomm Innovation Fellowship (QInF), now in its tenth year. We will be awarding fellowships of $100,000 to teams of two students. For the 2018 US edition, we invite proposals from 20 schools: Berkeley, Caltech, CMU, Columbia, Cornell, Georgia Tech, Maryland, Michigan, MIT, Princeton, Rutgers, Stanford, UCLA, UCSB, UCSD, UIUC, USC, UT Austin, Washington and Wisconsin.

 

We ask and appreciate your help in forwarding this information to Ph.D. students and faculty in EE, CE, CS and related areas. The attached flyer provides key details about the fellowship.

 

One of the members of Qualcomm Research will be reaching out to faculty members who we have worked with in the past, and visit your campus this month to hold an information session for the Ph.D. students.

 

The fellowship is open to Ph.D. students in the Electrical Engineering, Computer Science, Computer Engineering and related departments, who will apply for the fellowship by submitting their application. The Qualcomm Innovation Fellowship is based on Qualcomm core values of innovation, execution and partnership. The fellowship is only open to teams of two Ph.D. students. The proposal must be recommended by one or more faculty members.

 

The application deadline is November 12, 2017.

 

For detailed information, please visit: http://www.qualcomm.com/innovationfellowship

Any questions can be e-mailed to innovation.fellowship at qti.qualcomm.com <mailto:innovation.fellowship at qti.qualcomm.com> 

 

Qualcomm topics of interest include: 

 

We invite teams to submit proposals in the following areas. We also welcome proposals outside of the sub-areas listed below:

 

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

 

*         Autonomous Driving Machine Learning Advances in Communication Techniques and Theory 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.)

 

 

-- 

Chris Russo, MBA
Associate Director of Corporate Business Development
College of Engineering
Engineering II office 1508
University of California
Santa Barbara, CA 93106-5130
 
crusso at engineering.ucsb.edu <mailto:crusso at engineering.ucsb.edu> 
Office (805) 893-5544
Mobile (805) 280-2905
industry.ucsb.edu <http://industry.ucsb.edu> 
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