Facebook Fellowship Award Includes
- Tuition and fees paid for the academic year (up to two years/four semesters)
- $37K grant (one-time payment during each academic year)
- Up to $5,000 in conference travel support
- Paid visit to Facebook headquarters to for the annual Fellowship Summit
- Applicants must be full-time PhD students currently involved in on-going research who are enrolled in an accredited university in any country
- Students' work must be related to one or more relevant disciplines (see research areas below)
- Students must be enrolled during the academic year(s) the Fellowship is awarded
Applications Must Include
- 250-word research summary which clearly identifies the area of focus, importance to the field and applicability to Facebook of the anticipated research during the award (reference the research areas below)
- Resume or CV, with email, phone and mailing address, and applicable coursework noted
- Two letters of recommendation. Please provide reference email addresses. One reference must be from an academic advisor
Applications will be accepted from students with research related to one of the following areas:
We would like to support students who are working on novel techniques in statistical modeling and inference. Areas of research include but are not limited to inference in high dimensionals, causal inference, graphical models, sparsity and compressed sensing, pattern recognition, change detection, forecasting and time series analysis, optimization, regression, classification, clustering, graph partitioning, entity linkage and entity deduplication. Applications of interest include but are not limited to user modeling, detecting violations, experimentation, surveys or efficient sampling.
AR/VR Photonics and Optics
We would like to support students that are excited about developing technology in Photonics and Optics that can be applied to VR and AR visual systems. Topics of interest include functional planar optical elements, highly efficient light sources, optical and photonic imaging devices, unique optical materials and structures.
Computational Social Science
We would like to support students who are working on advancing research in the social sciences with computational approaches. Topics of interest include but are not limited to algorithmic fairness and bias correction, norms and trust, political participation, information cascades and influence, graph partitioning and community discovery, location aware social networks and mobility, theoretic and practical models and analysis of social networks, computer-mediated communication in dyads and groups, social processes after natural disasters and crises, well-being, social support, and mental health support.
We would like to support students who are working on advancing the state-of-the-art in computer graphics and efficient real-time rendering for augmented and virtual reality. Topics of interest include but are not limited to applications of machine learning methods, ray tracing and ray casting hardware, physically based shading, geometry processing and compression, image and video compression, perceptual rendering, high quality avatars, global illumination, scene prefiltering, and rendering complexity reduction.
We would like to support students who are working on advancing the state-of-the-art in computer vision. Topics of interest include but are not limited to image and video recognition (classification, detection, and segmentation), vision and language (visual question answering and visual dialog), visual reasoning (forward prediction, understanding physics, and understanding affordance), large-scale and weakly supervised learning, and understanding humans (pose estimation and action recognition).
Compute Storage and Efficiency
We would like to support students who are working on novel techniques for improving the efficiency of large scale systems such as databases, file systems, caching systems, pub/sub systems. This includes novel exploring techniques to shift computation, memory and storage with the goal of optimizing power consumption and/or cost.
We would like to support students working on a broad set of topics related to all kinds of distributed systems, including but not limited to fault tolerance, reliability, system management, scale, performance, efficiency, and security.
Economics and Computation
We would like to support students who are passionate about using mathematical and computational tools from the areas of game theory, optimization, operations management and econometrics. Topics of interest include but are not limited to theoretical and applied research that could help improve the design of mechanisms used to auction ads, optimize network infrastructure usage and processing power, improve processes such as procurement, hiring, and quality control, and understand the underlying processes, behaviors or incentives that align with real world observations.
Hardware and Software Infrastructure for Machine Learning
We welcome applications from students working on interdisciplinary research to support machine learning at scale. Research topics of interest include, but are not limited to, hardware and software techniques to improve machine learning inference and training in the datacenter or at the edge. Examples of projects include research targeting machine learning hardware specialization, compiler technologies for deep learning platforms, and techniques for distributed training/learning. We are also interested in research focused on workload characterization and performance analysis of real-world machine learning applications.
We would like to support students who are working on advancing the state-of-the-art in machine learning. Topics of interest include but are not limited to reinforcement learning, deep learning, causality, non-convex optimization, multi-task learning, curriculum learning, learning embeddings and metrics, speech recognition, cost-sensitive learning, and structured prediction.
Natural Language Processing
We would like to support students with topics of interest that include: machine translation, multilingual learning, representation learning, named entity recognition, text classification, semantic parsing, summarization, dialog systems.
Networking and Connectivity
We would like to support students active in the research and development of scalable, fast, reliable, and efficient systems across all areas of networking, including: different wired/wireless network domains such as data centers, backbones, peering, mobile core/backhaul, and access across many different parts of the spectrum (wifi to mmwave to optical); the whole stack, from chip/interface/system hardware design to low-level firmware to distributed systems; and the whole network lifecycle, from planning/design, to provisioning/deployment, to monitoring/troubleshooting/visualization, to control stacks.
Applications are welcome from students who are interested in the design and implementation of programming languages and related tools. Topics of interest include, but are not limited to: type systems, static analysis, optimizing compilation, runtimes, formal specification and verification, and high-level support for features such as concurrency, data privacy, control of side effects, and probabilistic and differentiable programming.
We would like to support students with established proficiency in the field and passion about solving complex security challenges. Topics of interest include but are not limited to: systems, software, and network security; privacy; cryptography; malware; abuse detection and mitigation; IoT security; authentication and authorization.
Spoken Language Processing and Audio Classification
We would like to support students working in speech and audio processing, particularly those advancing the state of the art in human-computer interaction, human-human interaction, and video content understanding. Topics of interest include but are not limited to speech recognition and synthesis, spoken language understanding, dialog systems, auditory scene analysis, acoustic event detection, audio-visual modeling and sentiment analysis.
We would like to support students who are working on understanding how online communities and technology use play a role in well-being. This includes, but is not limited to, research on how emotional affect, mental health, resilience, social support or other aspects of well-being relates to use of or participation in online communities, social media or technology more broadly.
Research outside the above: relevant work in areas that may not align with the research priorities highlighted above.