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Research Opportunities


**Note: The 2020 research opportunities are listed below. Prospective applicants are required to list their top six preferences in the online questionnaire via USAJobs.gov.

Applied Chemicals and Materials Division


647-1 Improving Our Understanding of Vapor-Solid Adsorption with Applications in Forensic Chemistry
Christopher Suiter and Megan Harries, 303-497-4027, cls3[at]boulder.nist.gov

When arson is suspected as a possible cause for fire, it is common for crime scene investigators to collect debris and place it into a cannister with an adsorbent carbon strip.  The carbon strip acts to capture volatile vapors emanating from the debris which are then tested by analytical methods to determine if an accelerant is present.  The SURF student will make measurements using NMR spectroscopy to improve the fundamental understanding of competitive vapor adsorption to solid materials, including carbon strips.  The student will also compare the adsorption behavior of hydrocarbon mixtures using static and dynamic head space sampling approaches.  Students with analytical/physical chemistry or chemical engineering backgrounds are encouraged to apply

647-2 Internal Consistency for Chemical Systems with Electrolytes Through Database Management
Vladimir Diky, 303-497-5273 diky[at]boulder.nist.gov
Achieving an internally consistent thermodynamic database is a challenging project. It requires compilation and maintenance of a large database of literature and transparent methods of evaluating experimental results. Our group applies consistent models of electrolyte behavior and chemical thermodynamic principles to build this database. Students with background in chemistry and experienced with Excel, graphics programs, and applying regression techniques are encouraged to apply.

647-3 Vapor Pressure Measurements of Aroma Compounds 
Jason Widegren, Tara Lovesteady, and Megan Harries, 303-497-5207, jason.widegren[at]boulder.nist.gov

Terpenes are a large group of volatile hydrocarbons produced by trees, medicinal plants, and some insects. They have many potential applications, including as natural agricultural pesticides, in the fragrance and flavoring industries, and even as alternative fuels. Designing and optimizing industrial processes for terpenes of interest requires knowing their vapor pressures. The SURF student will determine vapor pressures with a custom-built apparatus and will utilize gas chromatography with flame ionization detection. Students with analytical chemistry or chemical engineering backgrounds are encouraged to apply.

Public Safety Communications Research Division

671-1 Prize Competitions to Advanced Public Safety Communications Research
Joanne Krumel, 303-497-36834,joanne.krumel[at]boulder.nist.gov

PSCR’s Open Innovation Team launches prize competitions inviting innovators to solve problems and advance the research and development of communications technologies for first responders. (Search https://www.challenge.gov for NIST.) Upcoming competitions include: multi-modal data analytics, drone deployment, augmented reality, and Internet of Things. The SURF student will research concepts for new prize competitions; edit the OI Standard Operating Procedures; help draft the biennial White House report; develop targeted outreach lists; and research commercialization and business solutions. We are seeking a student with: interest in the federal government’s role in innovation and crowdsourcing solutions; exemplary oral and written communication skills; strong attention to detail and organizational skills; competence with Microsoft Office Suite; collaborative ethos; and customer service-orientation. Preferred, but not required, skills are: Excel skills at the intermediate or higher level; familiarity with Salesforce Customer Relationship Manager and Marketing Cloud or other enterprise email service.

671-2  Location Based Services, Visualizing real-time indoor tracking in 3D mixed-reality
Jeb Benson, 303-497-5191, jeb.benson[at]nist.gov

PSCR’s Location Based Services Portfolio is conducting research to help solve one of the ‘Holy Grails’ of public safety – tracking first responders operating indoors (see In Search of the Holy Grail: Indoor Tracking for First Responders for more info). One specific area PSCR is exploring is the fusion of real-time location data with 3D point clouds for visualization in a mixed-reality environment (e.g., the Microsoft HoloLens). In this project, the SURF student will be tasked with integrating real-time data from a localization system with mixed reality software to display live tracks. Potential areas of research include best practices, potential interoperability issues, and measuring user-experience. Preferred candidates will have experience in software development using Python, IoT, data analysis, and a willingness to produce a final paper summarizing findings.

671-3 Data Annotation Quality Assurance 
Craig Connelly and Gary Howarth, 303-497-3776, gary.howarth[at]nist.gov

This opportunity will require the intern to develop a new project focused on assessing the quality of data sets created specifically for an upcoming Open Innovation program. The data sets created for this program will include time synchronized video, audio, text, sensor, and other related multi-modal data in a continuous eight hour data set. The internship project will focus on creating a human review process to assess the quality of the data annotation within the data set, determine the overall accuracy of the data annotations, and document the review, assessment, and quantitative outcome of the process to be repeated on a regular basis. The preferred candidate will have: strong data management skills at the intermediate or higher level; ability to interact with data, manipulate data, analyze data, complete accurate data annotation, review data for quality, and other skills related to data heavy project or activities. In addition, a candidate will have quantitative analysis or statistics education or experience, experience with Python, R, or a similar software, and familiarity with multi-modal data sets (video, audio, sensor, text, time series).

671-4 Push to Talk Communications Quality of Experience Measurements in Python
Jesse Frey, 303-497-4056, jesse.frey[at]boulder.nist.gov

The Public Safety Communications Research (PSCR) Division’s Mission Critical Voice (MCV) team has developed a measurement system for quality of experience metrics in push to talk (PTT) communication systems.  This measurement system focuses on first responder communications systems as they look at transitioning to broadband communications on FirstNet.  The current system has been written in MATLAB; however, the MCV team is looking to rewrite the system in Python which is more widely used and freely available.  A SURF student will be responsible for porting a part of the measurement system from MATLAB to Python. The scope of the work will be determined by the student’s interests and abilities.  Candidates should have programming experience, preferably some with Python.  Interest or experience with audio playback and recording as well as signal processing is also preferred, but not required

671-5 Image Quality to Support America's First Responders
Scott Ledgerwood and Margaret Pinson, 303-497-5354, sal3[at]nist.gov

We are developing an algorithm that predicts the quality of an image or video, using only pixels. The SURF student will investigate quality of experience (QoE) and develop an algorithm. Working with a senior engineer, the SURF student will select a set of images that contain a single impairment at different levels of intensity. A panel of subjects will rate the quality of these images to create truth data. The SURF student will attempt to develop an algorithm in MATLAB that predicts the subjective assessment. Metric development support tools will be provided. The student will co-author a technical memorandum describing the dataset, which will be made available freely to encourage future algorithm development. The ideal candidate will have strong computer programming skills, exceptional math skills, knowledge of linear regression, and an interest in algorithm development.

671-6 3D Artist for VR/AR Development for Public Safety Scenarios
Jack Lewis, 303-497-6128, jack.lewis[at]nist.gov

PSCR’s User Interface/User Experience Team is seeking a creative, focused student to help develop 3D assets for virtual reality (VR) or augmented reality (AR) first responder scenarios. These scenarios will be used for prototyping future user interfaces such as heads-up displays, haptics, or audio cue style systems. The SURF student will have an opportunity to work alongside other NIST VR/AR developers as a 3D artist contributing to the construction of real-time virtual characters and environments to support public safety research. The preferred candidate should be experienced with the following skills: 3D modeling for real-time rendering pipelines, physically based rendering (PBR) material workflow, 3D sculpting, ability to take direction from senior artists and work within design constraints,  ability to follow project style guides and art direction software, Maya, Blender (or equivalent), Unity or Unreal (Unreal preferred), ZBrush,  Adobe Substance Suite,  Adobe Photoshop (desirable but not required), experience with Houdini and Houdini engine, and script knowledge.

671-7 IoT Data Security
Chris Nelsen, 303-497-3728, christopher.nelsen[at]nist.gov 

The rapid proliferation of internet-connected devices and rise of the Internet of Things (IoT) come with great anticipation.  These newly connected devices bring the promise of enhanced public safety information collection, sharing, and analysis.  Researching the processes to protect sensitive data will help ensure first responders cultivate trust in the innovative tools that are currently being developed.  A SURF student will research different scenarios, hardware, and processes for IoT data transmittal and storage to provide an in-depth analysis, demonstrating the risks associated with these processes.  This analysis will show the ability to compromise the data or provide access to unintended recipients, implications of the data being compromised, and best practices to implement these devices in a first responder community.  Special attention will be dedicated to how these risks affect law enforcement and justice system requirements for “chain of custody” for data collected from IoT devices.

Preferred candidates will have experience with programming languages; familiarity with networking and operating systems; some knowledge of cyber tools and devices; and a keen interest in cybersecurity.

RF Technology Division

 672-1 The Calibration Network
Nathan Orloff, 303-497-4938, orloff[at]boulder.nist.gov

We'd like to make a web-based utility (See http://calnet.nist.gov/) to help people measure materials. We are open to your ideas. A potential path might be a SQL database that's called from a WordPress website, which runs Python or MATLAB scripts on the server side. To feed the database with real data, we designed a materials characterization sticker. The sticker has several devices that one measures and then uploads the data to the web portal. Once the data is on the web portal the user can calibrate their data and obtain the dielectric constant of the material they are testing. We'd like SURF student to help us prototype this idea, which we call (tongue-in-cheek) the Calibration Network.

Applied Physics Division
 

686-1 The What If of Magnetic Resonance Fingerprinting
Megan Poorman, 303-497-3532, megan.poorman[at]boulder.nist.gov

MRI can be used to non-invasively quantify tissue properties within the body, but requires lengthy acquisitions to accurately measure properties, limiting its use in the clinic.  Magnetic Resonance Fingerprinting is a framework that combines fast MRI with physics modeling to quantify multiple properties simultaneously. However, there is little understanding of how hardware and software errors propagate throughout the system. In this project, the student will design and test MRI sequences under possible error cases in order to understand the measurement uncertainty. They will learn how to operate the NIST MRI and perform Monte Carlo analyses with parallel computing. Programming experience is recommended.

686-2 MRI and Microscopy on the Cellular Scale
Megan Poorman, 303-497-3532, megan.poorman[at]boulder.nist.gov

Magnetic Resonance Imaging (MRI) can be used to non-invasively quantify tissue properties within the body. Changes in the underlying cellular properties are a known source of variability in these measurements, as the resolution of MRI is much larger than the size of a cell. How cellular changes affect the MRI signal must be understood before quantitative MRI can be adopted into the clinic, yet few methods exist to validate it to the cellular scale. We are developing a living reference object capable of growing cells within the MRI and being monitored with both MRI and optical microscopy. The student will collect data on cell mimics with both MRI and microscopy, and work with collaborators to process images, model signals, and validate the measurements. Previous experience with cell culture and organized data management is a plus but not required.

686-3 Microwave Near-Field Imaging of One- and Two-Dimensional Nanoscale Materials
Mitch Wallis and Sam Berweger, 303-497-5089, mwallis[at]boulder.nist.gov

Emerging 1D and 2D nanomaterials are of fundamental interest for their unique quantum mechanical properties and will impact a wide variety of applications, including photonics, nanoelectronics, and advanced computation. We combine scanning probe microscopy with microwave techniques to perform electrical characterization and imaging of such novel materials with nanometer spatial resolution.  This opportunity will provide ample hands-on laboratory experience in atomic force microscopy (AFM), microwave electronic techniques, and image analysis. Some experience with AFM and/or scripting languages (matlab or python) is highly desirable.

686-4 Development of size-changing hydrogels for MRI-compatible sensor fabrication
Gary Zabow and Mark Ferris, 303-497-4835, mark.ferris[at]boulder.nist.gov

Opportunity Description: Smart hydrogels consist of three-dimensional networks of hydrophilic polymers that are functionalized to expand and contract in response to specific stimuli. By tailoring their monomer composition and curing conditions, hydrogels can be produced with specific mechanical properties and functionality for target applications. Recently, NIST developed a hydrogel-based, micro-scale sensor platform that enables, for the first time, deep tissue imaging of pH concentrations with magnetic resonance imaging (MRI). To expand the capability of this technology, the applicant will develop smart hydrogel formulations that are compatible with this MRI-sensor platform and responsive to biologically relevant analytes. Knowledge of hydrogels, polymer chemistry, and/or organic molecule synthesis is advantageous for applicants. In addition to hydrogel synthesis and characterization, this opportunity may also provide the student with experience in microfabrication technology and MRI analysis.

686-5 Novel MRI contrast and on-wafer MRI: RF and materials engineering to improve medical imaging
Stephen Russek, Karl Stupic, 303-497-4097, stephen.russek[at]boulder.nist.gov

New nanoengineered magnetic materials and spin manipulation techniques are required to enable better magnetic resonance imaging (MRI) contrast agents and new microMRI techniques. This opportunity explores a variety of nanoengineered magnetic materials that can provide novel MRI signatures including antiferromagnets, materials undergoing magnetic phase transitions, microfabricated thin film structures, as well as actively driven magnetic circuits.  One type of active magnetic circuit is an on-wafer nuclear-spin hyperpolarizer to enhance the signal in microMRI systems. The research will give experience operating an MRI scanner, fabricating magnetic thin film structures, design of software defined radio and microwave control circuits. The opportunity is perfect for physics, electrical engineering, bio, and materials science students who are interested in medical physics and engineering.

686-6 Building an optical access cryostat for measuring Si photoluminscence
Sonia Buckley, 303-497-6639, sonia.buckley[at]boulder.nist.gov

An on-chip, silicon-compatible light source has long been pursued for classical optical telecommunications without significant success. However, for applications where cryogenic operation is already required, for example, in quantum optics or neuromorphic or superconducting computing, point defects in Si may provide a suitable light source. The W center is a point defect in silicon with optical emission at 1.22 um for temperatures below 40 K. We have built an optical access cryostat for measurement of the photoluminescence from W centers in silicon. However, this cryostat produces excessive sample vibrations that limit the types of measurements it can be used for. The SURF student will help build a new version of the cryostat based on an updated design to mitigate these vibrations.

686-7 Quantum optics measurement and testing
Krister Shalm, 303-497-3094, lks[at]boulder.nist.gov

Our group performs measurements on quantum-entangled photons, and studies fundamental questions related to quantum mechanics. We have opportunities for a SURF student to develop laboratory skills in optics, high-speed electronics, cryogenics, and measurement automation.

686-8 Optical/microwave interface for quantum networks
Kevin Silverman, 303-497-7948, silverma[at]boulder.nist.gov

We are looking for a motivated undergraduate student with a strong physics background to participate in research related to emerging quantum networks. The successful candidate will work closely with lab members performing ultra-low temperature nanophotonics experiments. Specifically, our group is working with quantum dots and surface acoustic waves to convert quantum microwave signals into the optical domain without destroying the fragile quantum information. Hands on experience will be gained in some or all of the following areas; Dilution refrigerators, single-photon emitters, precision laser spectroscopy, and millikelvin microwave electronics

Quantum Electromagnetics Division

687-1 Modeling novel hardware for artificial intelligence
Michael Schneider, 303-497-3180, michael.schneider[at]nist.gov

Portable, trapped-atom-based instruments in battery-operable packages could bring about dramatic new applications in sensing, navigation, and communications.  Toward this goal, we are developing chip-scale trapped-atom platforms based on magneto-optical trapping.  A student working on this project will practice a broad range of techniques needed for the long-term development of compact trapped-atom systems, including lasers and optics, measurement methods, electronics, atomic theory, and vacuum systems.

Time and Frequency Division

688-1 Development of Chip-Scale Atom Traps 
Judah Levine, 303-497-3903, judah.levine[at]nist.gov

Portable, trapped-atom-based instruments in battery-operable packages could bring about dramatic new applications in sensing, navigation, and communications.  Toward this goal, we are developing chip-scale trapped-atom platforms based on magneto-optical trapping.  A student working on this project will practice a broad range of techniques needed for the long-term development of compact trapped-atom systems, including lasers and optics, measurement methods, electronics, atomic theory, and vacuum systems.

688-2 Explorations of Compact Atomic Clocks 
Juniper Pollock, Azure Hansen, 303-497-3370, azure.hansen[at]nist.gov

Portable, high-performance atomic clocks in battery-operable packages could bring about dramatic new timing applications in navigation and communications systems. Toward this goal, we are developing compact atomic clocks based on coherent population trapping. A student working on this project will practice a broad range of techniques needed for the long-term development of compact atomic clocks, including lasers and optics, measurement methods, electronics, atomic theory, laser cooling and trapping, and vacuum systems.


  

Created September 28, 2009, Updated January 10, 2020