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30 Dissertation Research Fellowships for Doctoral Students

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❶However, it has been always so hard to find that many of us had to write papers for academia by ourselves and get poor. This announcement represents the continuation of an AHRQ program that provides support to individuals who are conducting research undertaken as part of an accredited academic program to qualify for a research doctorate degree.

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The Geography and Spatial Sciences GSS Program sponsors research on the geographic distributions and interactions of human, physical, and biotic systems on Earth. Investigators are encouraged to propose plans for research about the nature, causes, and consequences of human activity and natural environmental processes across a range of scales.

GSS gives awards each year. Applicants need not be citizens of the United States; however, they must be candidates for the doctoral degree at a graduate school within the United States. These fellowships are designated for graduate students in any stage of Ph.

The fellowships, however, may not be used to defray tuition costs or be held concurrently with any other major fellowship or grant. Applicants may be of any nationality but must be enrolled in a U. Proposed research may be conducted at a single or multiple sites abroad, in the U. Research grants are awarded primarily to highly qualified PhD candidates who would like to conduct research in Germany. This grant is open to applicants in all fields. However, there are restrictions for those in healthcare related fields, including dentistry, medicine, pharmacy, and veterinary medicine; please contact the DAAD New York office if your academic pursuits are in these fields.

Applications accepted in November for month and short-term grants, and in May for short-term grants. The fellowship is for months, provides travel, health insurance and a monthly stipend of 1, Euros.

The fellowship lasts for months and provides travel, health insurance and a monthly stipend of 1, Euros. Candidates do not have to be U. The program offers support for graduate students, faculty, Ph. Scholars in the social sciences and humanities are eligible. Fellows can be doctoral students based at any academic institution in the United States and will be selected from a range of academic disciplines. Applicants must be a U. Kim Foundation provides fellowships and grants to support graduate students and young scholars who are working in the history of science and technology in East Asia from the beginning of the 20th century, regardless of their nationality, origins, or gender.

Comparative studies of East Asia and the West as well as studies in related fields mathematics, medicine and public health are also welcome. The Beckman Center for the History of Chemistry at the Chemical Heritage Foundation, an independent research library in Philadelphia, accepts applications for short- and long-term fellowships in the history of science, technology, medicine, and industry.

Applications come from a wide range of disciplines across the humanities and social sciences. Awards are made in all fieds. Applicants must have a well-defined research, study or creative arts project that makes a stay in Scandinavia essential.

Preference is given to those candidates who draw on the library and archival resources of more than one partner. It is required that each fellow spend a minimum of 3 days per week in residence in the Lillian Goldman Reading Room using the archival and library resources.

It is expected that applicants will have completed all requirements for the doctoral degree except for the dissertation. DeKarman fellowships are open to students in any discipline, including international students, who are currently enrolled in a university or college located within the United States. The fellowship is for one academic year and may not be renewed or postponed. Special consideration will be given to applicants in the Humanities.

The one-month fellowship is offered annually, and is designed to provide access to Yale resources in LGBT Studies for scholars who live outside the greater New Haven area.

Graduate students conducting dissertation research, independent scholars, and all faculty are invited to apply. The fellowship must take place between September and April. Health Policy Research Scholars is a national change leadership development opportunity for full-time doctoral students from underrepresented populations or historically disadvantaged backgrounds, entering the first or second year of their doctoral program, from any academic discipline who are training to be researchers and are interested in health policy research.

The Program is open to students in any discipline whose dissertation topics are within 19th — early 21st century Russian historical studies. Accordingly, my research has focused on the development of methods and algorithms that accurately model highly reverberant acoustic systems and process acoustic signals using as few parameters as possible.

Such accurate yet computationally efficient modeling and processing algorithms are of essential interest in a wide variety of applications ranging from virtual acoustics to healthcare. My main contribution is the development of algorithms, which rely on orthonormal basis functions and time-frequency representation of an acoustic system, that provide high accuracy over a wide range of frequencies in real-time. As an early demonstration, I propose an efficient solution to adaptive feedback cancellation problems.

Major advances in computer vision and mobile technologies have set the stage for widespread deployment of connected cameras, spurring increased concerns about privacy and security. Moving forward, I aim to leverage this framework to build low-power privacy-preserving computational cameras with camera-level implementations of learned encoding functions. Deploying AI systems safely in the real world is challenging. The rich and complex nature of the open world makes it difficult for machines trained on limited data to adapt and generalize well.

The errors that can result from an imperfect model can be extremely costly e. My research focuses on using human feedback to help reinforcement learning agents better adapt to the real world, leading to safer deployment of these systems. This involves developing robust models that can accurately predict uncertainty in the world, use different forms of human input to learn, and adapt quickly in real-time to new changes in the environment.

Developing such systems that learn from humans intelligently will move us closer towards more generalizable robots that perform a variety of tasks in such applications as assistive robotics, healthcare, and disaster response.

There has been a renewed focus on dialog systems, including non-task driven conversational agents i. Dialog is a challenging problem since it spans multiple conversational turns.

To further complicate the problem, there are many contextual cues and valid possible utterances. We propose that dialog is fundamentally a multiscale process, given that context is carried from previous utterances in the conversation. Neural dialog models, which are based on recurrent neural network RNN encoder-decoder sequence-to-sequence models, lack the ability to create temporal and stylistic coherence in conversations.

My thesis focuses on novel hierarchical approaches to improve the responses of neural chatbots. To that end, modern network devices offer programming interfaces for fine-grained specification of what information to maintain across packets, and how to process packets based on it.

My thesis focuses on designing programming platforms that facilitate the use of programmable network devices for large-scale and real-time network monitoring and control.

More specifically, these platforms consist of i domain-specific languages that are expressive enough for high-level specification of policies for end-to-end network transport, network-wide state-aware monitoring and control, and path-based network monitoring, and ii compilers that use efficient intermediate data structures to automatically distribute and implement these specifications on programmable network devices. I aim to develop methods to help users of machine learning models increase both the trust in and understanding of their models.

My dissertation is in the two fields of interpretability and causal inference. The two fields, seemingly disparate, actually share the common goals of revealing and adjusting for biases that can arise when building machine learning models.

In causal inference, I have worked on methods that use machine learning to more flexibly estimate treatment effects from observational data. To complete my dissertation, I plan to probe the definition of interpretability — still a subject of debate in machine learning — by conducting a large-scale comparison of different models claimed to be interpretable and augment this quantitative evaluation with human subject experiments using domain experts.

Ebuka Arinze Johns Hopkins University. Nanoengineering for Tunable Energy-Efficient Optoelectronics. Colloidal nanomaterials, such as semiconductor quantum dots, are of interest for various optoelectronic applications due to their size-tunable optical properties, distinctive electronic structure, and low-cost fabrication.

Color-tuned and semi-transparent photovoltaics, devices with controlled and tunable reflection and transmission spectra, are of significant interest due to their potential applications in building-integrated photovoltaics, vehicular heat and power management, and multijunction photovoltaics.

My project focuses on using nanoengineering techniques, including multi-objective optimization algorithms, plasmonic nanoparticle enhancements, and hybrid-materials-based surface modifications, to design and build colloidal quantum dot-based devices with controlled optical and electrical properties for the next generation of inexpensive and ubiquitous light harvesting, detection, and emission technologies.

These algorithms allow us to specify data collection tasks, e. To reduce the amount of data needed for each task, and since models of underwater dynamics are computationally expensive, we use model-based reinforcement learning techniques where the models are data-driven. A problem with these approaches is that, even if they are data efficient, collecting new data is expensive. Adopting cloud services to reduce operational, maintenance and storage costs, is becoming increasingly common.

However, outsourcing data and computations, is opening up new challenges in terms of integrity and privacy of the data and the computations on them. Along with such important security and privacy concerns, availability, and scalability are major factors in such settings. My thesis addresses various problems in this space of secure storage and computation outsourcing. In summary, the main contributions of my thesis are the following.

The beginning of a new era in safe assistive robotics will occur when people with disabilities and seniors let intelligent software control a mobile robotic manipulator to safely reposition their body and limbs. Our goal is to explore the intersection between providing physical care and robotics, and how it is possible to translate safe patient handling and mobility guidelines into smart human-robotic interaction HRI algorithms. For a mobile manipulator with knowledge-managed algorithms.

Our efforts seek to standardize protocols and regulations for how artificial intelligence agents related to physical HRI can achieve body and limb repositioning tasks. As assistive robotics become more mainstream, these best practices can improve safety in direct physical care in the process of repositioning the human body with a mobile robotic arm.

My research primarily focuses on exploring how machine learning can help improve real world decision making in domains such as health care and criminal justice. To this end, my thesis addresses various challenges involved in developing and evaluating interpretable machine learning frameworks which can complement and provide insights into human decision making.

More specifically, my thesis focuses on the following diverse yet related research directions: The main contribution of my thesis is to address these problems under realistic assumptions which hold in real world decision making such as presence of unmeasured confounders and limited availability of labeled data. My study examines the implementation of the health information system HIS in Mozambique and the roletechnologies play in educating health professionals for better delivery of care.

Through a comprehensive examination of the HIS, from development to roll-out, I analyze the relationship between colonial and post colonial governmental top-down policies and compare them to the on-the-ground reality of using information and communications technology ICTs to provide health education given social, economic, and political realities in Mozambique.

Part of the problem with studies of technologies in poor parts of the world is that they are often conducted by highly educated researchers and are conducted in English. However, majority of the population in poor nations does not speak English. Such studies become irrelevant to the life experiences of those being studied.

I will disseminate findings from this study in Portuguese and English through talks and publications in U. Touch-enabled devices such as smartphones, tablets, and interactive kiosks are some of the most pervasive technologies in the world today. As a result, touch has emerged as one of the most dominant forms of input for computing devices. My dissertation research takes an ability-based design approach toward improving the accessibility of touch-enabled devices for people with motor impairments.

I intend to create intelligent interaction techniques that allow people with motor impairments to touch in whichever ways are most comfortable and natural for them, and for the system to react as if it was touched precisely. In this era of increased engagement with technology, many latency-sensitive applications processing large amounts of data have emerged. For example, we expect social networks to show hashtag trends within minutes, data from IoT to be processed within seconds, and online gaming to react within milliseconds.

In all these diverse areas, handling large scale data in a real-time fashion is crucial. At scale, providing low latency becomes increasingly challenging with many complexities in distribution, scaling, fault-tolerance, and load-balancing.

My research has focused on developing techniques that broadly explore these issues with particular attention to end-to-end latency and building massive-scale solutions.

Most of my work is deployed in large-scale production systems with hundreds of millions of users. My research contributions span a wide range of frameworks including: My dissertation work attends to the intersection of accessible human-computer interaction and video game design. Games continually grow more complex, pervasive, and significant in 21st century life. Therefore, my work proposes to understand the play experiences of gamers with impairments and offer novel design solutions for mitigating the accessibility barriers they face.

My proposed investigations seek to understand how accessibility barriers manifest in mainstream games, to empower gamers with impairments to better navigate the landscape of game accessibility through novel information design, and to address underlying institutional concerns that perpetuate systemic accessibility issues in the game development industry through education interventions.

Applications of Heterodox Rendering Methods to Visualization. Information visualization is an illustrative method to depict data, and the structure of this data is not necessarily known beforehand.

The classic rendering via rasterization of visualization primitives tends to minimize extraneous details; every drawn pixel or glyph has a tight correspondence to the data on which it is based. A simple line chart for example. It is thought that a more expressive or artistic rendering of data might harness additional insight through abstraction, or even an emotional connection.

These expressive methods which I have classified as Heterodox Visualization HV methods, include non-photorealistic rendering NPR , stylized rendering processes like pixelization, and other rendering approaches, like those that mimic natural media e.

To date there has been little systematic guidance covering how these HV methods could be applied to information visualization. My research will help determine, through experiment, which techniques pose a benefit to different types of visualizations. My research focuses on designing wireless communication protocols for Internet-of-Things IoT applications that require low-latency and high-reliability. I am developing wireless communication protocols that employ simultaneous relaying by all radios in the network.

This allows us to overcome bad channels and guarantee the latency requirements.

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Call for Dissertation Grant Proposals AERA Grants Program Seeks Proposals for Dissertation Grants Deadline: October 17, With support from the National Science Foundation, the American Educational Research Association (AERA) Grants Program seeks proposals for Dissertation Grants.

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Dissertation Grants. Dissertation research grants of up to $5, support current graduate students whose scholarship focuses on free societies and the ideas, institutions, and values that contribute to maximizing well-being.

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• Investigate federal funding sources. For most students, it might seem like a long shot, but your dissertation research might be a good fit to the research interests of an institute of the National Institutes of Health, which offers two grant programs for students. With funding from the National Science Foundation (NSF), the American Educational Research Association (AERA) is pleased to announce the continuation of the AERA Grants Programs. Applicants for Dissertation and Research Grants may be U.S. citizens or U.S. permanent residents enrolled in a doctoral program or have received the .

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The Kauffman Dissertation Fellowship (KDF) is an annual competitive program that awards up to 20 Dissertation Fellowship grants of $20, each to Ph.D., D.B.A., or other doctoral students at accredited U.S. universities to support dissertations in the area of entrepreneurship. The maximum amount of the Dissertation Fieldwork Grant is US $20, Please note that the Foundation has suspended the Osmundsen Initiative supplement Grants are non-renewable. Students must be enrolled in a doctoral program (or equivalent, if applying from outside the United States) at the time of application.