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The following research projects are currently in need of dedicated Postdoctoral Fellows to complete their work. To be a
candidate for any of the projects, you must be a U.S. citizen and have received your PhD by the fellowship start date. These
listings are for information only. Applications must be made to the University and Principal Investigator directly.
| Status: OPEN |
Added: 11/02/2009 12:00 AM |
| Research Area: Identifying Carbohydrates Specific to Francisella Tularensis for the Purpose of Improving Detection of Aerosolized Biological Weapons |
Project Description:
Job ID: 117337
Pacific Northwest National Laboratory: Richland, WA
Department Name: Chemical and Biological Signature Sciences
Job Description
A highly motivated candidate is sought to fill a prestigious IC Postdoctoral Research Fellowship Program position in carbohydrate biochemistry at Pacific Northwest National Laboratory (PNNL). Analytical methods will be developed for the isolation and purification of glycans. Identification and structural determination will be performed using mass spectrometry techniques including MS/MS, MSn,l and accurate mass measurements. Initial studies will be directed toward glycan signatures that discriminate pathogenic microorganisms from closely related species or between cultivated and naturally occurring species. The fellowship provides full support for 2 years with an optional third option. Additional information about the fellowship program is available at http://www.icpostdoc.org.
Requirements:
Minimum Requirements
A U.S. citizen who has recently graduated (or will be graduating by the fellowship start date) from an accredited Analytical Chemistry and/or Microbiology Ph.D. program within the last five years. All staff at PNNL must be able to demonstrate the legal right to work in the U.S.
• Experience in carbohydrate chemistry is preferred.
• Experience in mass spectrometry both LC/MS and GC/MS is preferred.
• Experience in separations and isolation of carbohydrates is preferred.
• Experience in bioinformatics is preferred.
Equal Employment Opportunity
PNNL is an Affirmative Action/Equal Opportunity Employer and supports diversity in the workplace. All employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, veteran status, marital or family status, sexual orientation, gender identity, or genetic information.
If you are interested in joining this research project as a Postdoctoral Fellow, please contact:
To Apply: Please log on to the PNNL job site at http://jobs.pnl.gov, then search for and apply to open requisition #117337.
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| Status: OPEN |
Added: 08/12/2009 12:00 AM |
| Research Area: Modeling Leadership and Collective Behavior of Tribal Culture |
Project Description:
Sociologists have described culture as a process of development from primitive cultures to clans (tribes) to highly developed societies. On this continuum, researchers focus on various organizing variables such as type of leadership: charismatic vs. ruled-governed or level of development in societal systems as represented by the system of finance. For example, does lending exist in an institutional setting or a private system among tribe members? New and novel approaches have recently been reported in the literature that add to the body of knowledge regarding leadership in tribal cultures, and the dynamics of change in leadership and conditions (such as violence), that are brought about by change. One new approach by Lim et al. is global pattern formation that begins to develop a theory of collective behavior of tribal leadership based a geospatial approach using census data. Lim and colleagues focus on some variable such as violence that is brought about in emerging nations. Yugoslavia and India have been modeled using this new and innovative spatial approach. There is a small but growing literature in this area that seeks to create a body of knowledge and provide descriptions of tribe culture in the context of war and conflict both with other tribes and with highly differentiated, technology based cultures such as that of the United States.
Technical Objectives:
The Postdoctoral Fellow will conduct a systemic literature review of open sources using Pakistan and Afghanistan as the case studies that would identify drivers of change, and identify theories that have the capability to generate predictions about the socio-cultural dynamics between different levels of cultural development. In addition to exploring the dynamics among tribes, it is equally important to examine drivers and dynamics between tribes and nations (Pakistan) that are more culturally differentiated. The Postdoctoral Research Fellow will:
• Collaborate with Sandia Principle Investigators and other staff to develop a database of social, cultural, historical, political factors that will form the basis of the decision rules, assumptions, and parameters for the analysis;
• Analyze the strengths and weaknesses using a network approach that could be instantiated in a simulation tool;
• Identify other non-network, novel approaches from the literature that could predict collective behavior and decision making by tribe leadership; and
• Apply this knowledge and perform an analysis of three tribal cultures in Pakistan or Afghanistan.
Requirements:
A U.S. citizen who has recently graduated (or will be graduating by the fellowship start date) from an accredited Ph.D. program within the last five years and is interested in working as a Postdoctoral Fellow at Sandia National Laboratories.
The ideal candidate will have experience in a field of the social sciences (sociology, anthropology) to help begin an interdisciplinary research program that blends expertise from the engineering, computational and social sciences to modeling of leadership and by extension, decision making at the tribal level of cultural development.
If you are interested in joining this research project as a Postdoctoral Fellow, please contact:
Sandia National Laboratories' website. You must first submit a resume through the Careers section listed below. To access the job description, please enter 62601 in the job search keywords field:
https://ws03snlntz.sandia.gov/psp/applicant/EMPLOYEE/HRMS/c/HRS_HRAM.HRS_CE.GBL
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| Status: OPEN |
Added: 08/04/2009 12:00 AM |
| Research Area: Unique Solvents for Identification of Dyes in Wool Fibers |
Project Description:
This project aims to explore new methods for the high efficiency extraction of dyes from wool and other natural protein fibers utilizing unique solvents. The solvents are suitable for direct analysis using either MALDI-TOF-MS or LC-MS/MS technique for the identification of dyes extracted from the fibers, as well as quantification. These new solvent systems and combined techniques will be compared to existing LC-MS and CE-MS systems in terms of efficiency, integrity, and accuracy.
Technical Objectives:
The type of textile fibers and dyes found as evidence at crime scenes can provide significant information regarding the source of that fiber. The identification of the many components to the color of dyed fibers is critical to identifying where the fabric originated. Currently, efficient methods exist for characterizing the dyes used in synthetic fibers such as polyester and cotton utilizing extraction with aqueous and organic solvents, followed by separation of the dye through liquid chromatography (LC, TLC, HPLC) or capillary electrophoresis (CE) and analysis by UV-visible spectrophotometry or mass spectrometry (MS). However, analogous extraction and analytical methods for natural fibers such as wool and silk are not as effective due to the strong interactions that occur between the fibers and dyes, and common apolar dyes used. Wool is comprised of the protein keratin, containing amino acids allowing multiple interactions with dyes. The binding of the dye is typically through electrostatic interactions, but contain hydrogen bonding and hydrophobic interactions as well, making aqueous extractions ineffective. This project will address the development of a new method for the efficient extraction of dyes from wool fibers for the forensic analysis of the dyes present, and compare to possible origins and sources. The method and analyses performed will be compared to existing technologies, and aid in advancing the area of highly effective and precise identification of textile dyes. These efforts will provide possible new technologies to assist investigative efforts of criminal and terrorist sites.
Requirements:
A U.S. citizen who has recently graduated (or will be graduating by the fellowship start date) from an accredited Ph.D. program within the last five years and is interested in working as a Postdoctoral Fellow at Los Alamos National Laboratory.
If you are interested in joining this research project as a Postdoctoral Fellow, please contact:
Dr. Rico E. Del Sesto, Principal Investigator
Los Alamos National Laboratory
Los Alamos, NM 87545
Phone: (505) 665-9087
Fax: (505) 667-9905
Email: ricod@lanl.gov
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| Status: OPEN |
Added: 07/20/2009 12:00 AM |
| Research Area: LIDAR Compressed Sensing Using Prior Information |
Project Description:
This research will investigate the use of compressed sensing (CS) with prior information at the data acquisition stage of LIDAR sensors. The objective is to show how prior information on the support region of the sparse domain of LIDAR signals can be added to the sampling and reconstruction procedures. The use of prior information can have advantages in terms of number of required measurements (or percentage of correct reconstructions), number of iterations and convergence time. LIDAR sensors are used to produce accurate and high-resolution data in airborne remote sensing by collecting millions of measurements per second. A combination of data collected from a laser scanner (LIDAR), an inertial reference system (IRS) and a global positioning system (GPS) are used to produce accurate digital topographic maps of the terrain beneath the flight path of an aircraft. Although the acquisition hardware used in such laser scanning systems is in a mature stage of development, the research on image processing software to ease the demands for transmission and storage of such systems is still in its early stage.
Technical Objectives:
The main research activities executed by the Postdoctoral Research Fellow include:
• Becoming familiar with the CS approach, the LIDAR data and their characteristics in terms of probabilistic models, power spectral and multiscale contents
• Implementing algorithms to extract prior information from the LIDAR data and to classify the data according to their associated rural/urban content
• Implementing a new scheme to incorporate prior information
• Implementing the required changes to optimize the transformation to the scene content
• Evaluating and adjusting the CS technique to make it potentially more robust to noise, spurious returns, clutter and features of varying scale
• Implementing intensive tests
• Evaluating the computational demands, artifacts introduced by the CS algorithm.
The Fellow will work under the PI’s supervision and receive direct assistance from one Master student also working in the project, as well as from other research assistants currently working with the PI. The Fellow will receive support for working on the research, developing Matlab programs, running simulations, working on journal papers, preparing presentations for the IC Postdoctoral Research Fellowship Program’s annual Colloquium, and preparing partial and final reports.
Requirements:
A U.S. citizen who has recently graduated (or will be graduating by the fellowship start date) from an accredited Ph.D. program within the last five years and is interested in working as a Postdoctoral Fellow at the University of Texas at El Paso.
The ideal candidate’s expertise could include compressive sensing, statistical estimation, optimization, numerical methods, wavelets, and LIDAR systems. Candidates in engineering, applied mathematics, and statistics are welcome to apply.
If you are interested in joining this research project as a Postdoctoral Fellow, please contact:
Dr. Ricardo von Borries, Principal Investigator
University of Texas at El Paso
El Paso, TX 79968
915-747-7959
rvonborries@utep.edu
http://orspprofile.utep.edu/profilesystem/editprofile.php?onlyview=1&pid=1629
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| Status: OPEN |
Added: 07/13/2009 12:00 AM |
| Research Area: Nonlinear Estimation Methods for Geolocation of Hand-Held Video |
Project Description:
Remote Sensing image registration objectives for the Intelligence Community are challenging because of the need for geolocation based on multiview, multitemporal, and multimodal images. Feature tracking between similar views is an available technology. However, these methods are particularly challenging to apply when comparing a near Nadir image with a hand-held video because there may be few groups of features that correspond in a manner that facilitates template matching. The aim in this project is to develop new methods to generate geometric maps of scenes acquired from an arbitrary video. The approach is to exploit new estimation methods to attach a reference frame to surfaces containing feature points. One method uses the Euclidean Homography derived from two images, in conjunction with a human assisted estimation of a single geometric length between two feature points. Daisy-chaining methods will then be used to propagate the geometric length throughout the video to generate a geometric map. The second method aims to solve the ambitious structure and motion estimation problem whereby a nonlinear implicit learning estimator coupled with an adaptive estimator are used to simultaneously determine the motion of the camera, and the geometric map of the video scene.
Successful completion of the project will lead to a new understanding of how to embed a geometric length into video sequences taken from an arbitrary video source. The ability to embed some geometric length in the video allows for scene mapping, providing an inroad to automated image registration and geolocation with respect to some reference maps. The methods provide a new solution to the geolocation problem that may be particularly suited to needs of the remote sensing intelligence community because they are applicable to different imaging sources from different perspectives (i.e., information from a handheld camera compared to information from near Nadir satellite images).
Requirements:
A U.S. citizen who has recently graduated (or will be graduating by the fellowship start date) from an accredited Ph.D. program within the last five years and is interested in working as a Postdoctoral Fellow at the University of Florida.
If you are interested in joining this research project as a Postdoctoral Fellow, please contact:
Dr. Warren Dixon, Principal Investigator
University of Florida
Gainesville, FL 32611
352-846-1463
wdixon@ufl.edu
http://ncr.mae.ufl.edu/index.php?id=people
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| Status: OPEN |
Added: 07/13/2009 12:00 AM |
| Research Area: Statistical Evaluation of Error Rates for Graph-Based Identification Technologies |
Project Description:
Graph-based technologies have proven to be an effective method for dealing with the complexities of handwriting biometric data. These methods have demonstrated high accuracy rates in a number of languages. Preliminary research has also demonstrated that graph-based technologies can be applied to other biometric modalities besides handwriting. An important tool for extending graph-based methods to new modalities is the ability to provide a statistical estimate of the accuracy of the procedure. The accuracy of the method will depend upon the quality of the quantification procedure and the ability of the statistical component of the classifier to use the information retained in the quantification procedure. The accuracy of a classification method or the corresponding error rates are parameters that can be statistically estimated. The primary activity of the proposed research is to develop a standard set of tools to estimate the accuracy of a classification procedure. This research will facilitate the development and extension of graph-based quantification technologies to new modalities, thereby providing concrete guidance on the improvements gained or not gained over traditional methods.
Requirements:
A U.S. citizen who has recently graduated (or will be graduating by the fellowship start date) from an accredited Ph.D. program within the last five years and is interested in working as a Research Assistant Professor with the Intelligence and Security Research Center at George Mason University.
If you are interested in joining this research project as a Postdoctoral Fellow, please contact:
Dr. Christopher Saunders, Principal Investigator
George Mason University
Fairfax, Virginia 22030
703-993-9333
csaunde6@gmu.edu
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| Status: OPEN |
Added: 07/13/2009 12:00 AM |
| Research Area: Multi-Photon Fock State Microscopy at the de Broglie Wavelength |
Project Description:
Nonclassical multi-photon states have been suggested towards high resolution quantum phase measurement and imaging, where indistinguishable N photons possess a de Broglie wavelength of ?/N for high resolution quantum measurements and microscopy. Particularly, research has recently demonstrated – in both experiments and theory – a four-photon state with phase precision beating the standard quantum limit and approaching the Heisenberg uncertainty. Supported by theoretical and experimental results on multi-photon entangled states and high resolution phase measurements near the Heisenberg limit, the research will theoretically examine feasible experimental schemes to achieve high resolution microscopy with efficient photon state generation and compact photon measurement. The schemes developed will be robust and examined against decoherence. The researcher’s theoretical expertise, coupled with the experimental results achieved, will enable the practical development of effective multi-photon Fock state schemes for high resolution microscopy at the de Broglie wavelength.
Technical Objectives:
In this project, the Postdoctoral Fellow will first examine the production of multi-photon states and discuss their application to high-precision microscopy. Secondly, the postdoctoral researcher will examine the effects of decoherence of the multi-photon state towards beating the standard quantum limit in the imaging resolution.
Requirements:
A U.S. citizen who has recently graduated (or will be graduating by the fellowship start date) from an accredited Ph.D. program within the last five years and is interested in working as a Postdoctoral Fellow at Columbia University.
If you are interested in joining this research project as a Postdoctoral Fellow, please contact:
Dr. Chee Wei Wong, Principal Investigator
Columbia University
New York, NY 10027
212-854-4275
cww2104@columbia.edu
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| Status: OPEN |
Added: 07/13/2009 12:00 AM |
| Research Area: Advanced Electrical Metrology for Nanoelectronic Device Characterization |
Project Description:
Due to the continued scaling of the individual devices in integrated circuits to ever smaller dimensions, the component capacitance of these nm-scale devices defy easy measurement. Emerging nanoelectronic devices for information processing such as memristors and circuits based upon crossbar architectures have capacitances that are much smaller than those measurable by conventional LCR meters. The interior device capacitances of these deep-submicron devices determine the operational characteristics of the device and an accurate knowledge of their values is required for accurate device modeling and predictive computer-aided design. Thus, an effective method to experimentally extract these capacitances will have an immediate technological impact.
Technical Objectives:
The “memristor” is a fascinating new device that holds great promise for advanced information processing applications such as ultra-low power memory and logic, high-performance field-programmable arrays, or adaptive analog circuitry. The Postdoctoral Fellow will develop advanced capacitance measurement techniques that will help speed the development, assessment, and deployment of this promising new memristor technology. The Fellow will apply these advanced capacitance measurement techniques for the quantitative measurement of small (aF-scale) capacitances of perhaps the most promising of the new nanoelectronic devices, crossbar arrays of TiO2–based “memristor” devices. These measurements will assess the capabilities and performance of these structures as well as provide an understanding of the fundamentals of charge transport within them. While these precision capacitance measurements are important for the rapid development and adoption of memristor technology, the methods developed will also have a broad impact on a variety of other important nanotechnologies such as next generation, deep sub-100 nm CMOS (complementary metal oxide semiconductor) technologies and those based upon nanowires and nanotubes.
Requirements:
A U.S. citizen who has recently graduated (or will be graduating by the fellowship start date) from an accredited Ph.D. program within the last five years and is interested in working as a Postdoctoral Fellow at the National Institute of Standards and Technology.
If you are interested in joining this research project as a Postdoctoral Fellow, please contact:
Dr. Curt A. Richter, Principal Investigator
National Institute of Standards and Technology
Gaithersburg, MD 20899
301-975-2082
Curt.Richter@NIST.gov
http://www.nist.gov/eeel/semiconductor/cmos/richter.cfm
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| Status: OPEN |
Added: 07/13/2009 12:00 AM |
| Research Area: Computing Pairwise Similarity on Large Text Collections with MapReduce |
Project Description:
The University of Maryland is seeking an energetic Postdoctoral Fellow at the intersection of information retrieval and natural language processing for research on large-scale document analysis using the MapReduce programming model. This is an excellent opportunity to work in the emerging area of "cloud computing" to tackle text processing problems at scale. This is a joint position between the College of Information Studies (the iSchool) and the Institute for Advanced Computer Studies. The Postdoctoral Fellow will be a member of the Laboratory for Computational Linguistics and Information Processing (CLIP), a large, multi-disciplinary research group with strengths in statistical machine translation, summarization, question answering, information retrieval, and other human language technologies. CLIP is active in cloud computing, and maintains strong ties to industry and government. The proposed research will attempt to leverage Hadoop, an open-source implementation of Google’s MapReduce programming model, to tackle the problem of computing pairwise document similarity with distributed text processing algorithms. These algorithms support approximations that control tradeoffs between effectiveness (accuracy of similarity scores) and efficiency (running time), allowing adaptation to different usage scenarios. Implemented algorithms will be demonstrated on applications jointly agreed upon between the IC advisor and the principal investigators.
Requirements:
A U.S. citizen who has recently graduated (or will be graduating by the fellowship start date) from an accredited Ph.D. program within the last five years and is interested in working as a Postdoctoral Fellow at the University of Maryland.
The successful candidate will have a strong track record of productive research and successful implementation in information retrieval, language technology, text mining, or related areas. Previous research with a focus on scalability and algorithmic efficiency would be highly valued, and some experience with MapReduce would be a plus.
If you are interested in joining this research project as a Postdoctoral Fellow, please contact:
If you are interested in joining this research project as a Postdoctoral Fellow, please send a CV, contact information for three references (including email addresses), and a description of your research agenda to:
Dr. Jimmy Lin or Dr. Doug Oard, Principal Investigators
University of Maryland
College Park, MD 20742
301-405-6518
jimmylin@umd.edu
oard@umd.edu
http://www.umiacs.umd.edu/~jimmylin/
http://terpconnect.umd.edu/~oard/
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| Status: OPEN |
Added: 07/13/2009 12:00 AM |
| Research Area: Passive Methods for Internet Topology Discovery |
Project Description:
The project proposes to develop large-scale Internet maps via a wholly new approach. Whereas previous methods for Internet topology discovery have relied on active probing (injecting traffic into the network), this project will develop methods for inferring Internet topology from passively collected data. In support of this, the project will collect data from a wide variety of passive traffic collectors. The inference methods contemplated are based on data (such as hopcount) that is already present in passively collected data. The methods developed will extend and build on the methods already developed by the PI. The successful completion of this project will yield a new repository of Internet topology data of unprecedented scope, and new methods that can be applied to individual networks of interest for large-scale topology discovery.
Requirements:
A U.S. citizen who has recently graduated (or will be graduating by the fellowship start date) from an accredited Ph.D. program within the last five years and is interested in working as a Postdoctoral Fellow at Boston University.
If you are interested in joining this research project as a Postdoctoral Fellow, please contact:
Dr. Mark Crovella, Principal Investigator
Boston University
Boston, MA 02245
617-353-8923
crovella@cs.bu.edu
http://www.cs.bu.edu/~crovella/
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| Status: OPEN |
Added: 07/13/2009 12:00 AM |
| Research Area: DNA Profiling of Soil Microbial Metagenomic Signals Using High-Density Microarrays |
Project Description:
The goal of this proposal is to enhance the toolset available to forensic scientists by developing an additional tool for examining soil deposited on items from diverse locations. The proposed research will create a set of DNA markers that generate a repeatable and identifiable pattern distinguishing diverse locations. This project will use computational and laboratory tools in a systematic study to develop and test a set of DNA profiling markers, and to determine the feasibility of using them as a barcode for distinguishing geographical locations or important environmental sample types. It will heavily leverage the past and current investments by OCS in LLNL bioinformatics analysis capabilities, and investments by DHS and LLNL in high-density microarrays for microbial identification.
Technical Objectives:
The proposed work will utilize mature existing microarray development, fabrication and testing capability at LLNL to generate sets of up to 385,000 DNA markers that can be used to profile soils. The PI and Fellow will explore different mixes of bacterial, viral, and random DNA markers to attempt to determine highly differentiating patterns from diverse soil samples. The project will also consist of testing a range of soil types and sampling locations to achieve statistically-meaningful preliminary results of the feasibility of this novel forensic technique.
Requirements:
A U.S. citizen who has recently graduated (or will be graduating by the fellowship start date) from an accredited Ph.D. program within the last five years and is interested in working as a Postdoctoral Fellow at Lawrence Livermore National Laboratory.
If you are interested in joining this research project as a Postdoctoral Fellow, please contact:
Thomas Slezak, Principal Investigator
Lawrence Livermore National Laboratory
Livermore, CA 94550
925-422-5746
Slezak@LLNL.gov
http://*people.llnl.gov/slezak1
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