Reference Code: 501

Posted: 10-08-2021

Location:
Army Cyber Institute, United States Military Academy, Spellman Hall, 2101
New South Post Road, West Point, New York 10996.

Duration:
Immediate availability (start date negotiable), 12 month appointment (potential for extension)

Fellowship Offering Type: 
Post-Doctoral

Detailed Lab Description, Background and Research Focus:
The Army Cyber Institute (ACI), is a national resource for interdisciplinary research, advice and education in the cyber domain, engaging DoD, Army, Government, academic and industrial cyber communities in impactful partnerships to build intellectual capital and expand the knowledge base for the purpose of enabling effective army cyber defense and cyber operations. The next-generation battlefield will be populated with a vast number of interconnected, heterogeneous and sometimes autonomous agents including devices, networks, software, and humans. Defending such complex and/or autonomous systems will be impossible for humans to do alone, making research in this area key in defending such system.

In response to the challenges facing the Cyber and Information Domain, our projects support the research, development, experimentation, testing, evaluation and operationalization of computationally intelligent, assured (secure, resilient, robust, safe, trusted), and distributed decision-support systems for autonomous cyber operations in highly-contested, complex battlefield environments. To build, assess and deploy smart, autonomous cyber-systems that enable intelligent, assured and federated decision-making, our research explores the science of information, computation, learning, and fusion for adaptive, collaborative pattern discovery, reasoning, perception, action and decision-making given heterogenous, complex, disparate data spanning devices, networks, software, and humans.

Overall, our research aims to develop models and tools for collective intelligence, likely augmented by interacting with human cyber analysts and decision-makers. As such, we conduct basic and applied research and development with the objective of providing new capabilities to: shift emphasis from sensing to information awareness; understand the underpinning of autonomy; relieve human cognitive overload in dealing with the data deluge problem; enhance human-machine interface in information processing; cope with various complex disparate data/information types; integrate a diversity of unique reasoning and learning components collaborating simultaneously; bridge correlational with causal discovery; determine solutions or obstructions to local-to-global data fusion problems; mechanize reasoning/learning and computing in the same computational environment; yield provably efficient procedures to enable or facilitate advanced data analytics; and deal with high-dimensional and massive datasets with provably guaranteed performance.

Fellowship Project Description:
The Army Cyber Institute (ACI), United States Military Academy (USMA) at West Point, NY is looking for a Postdoctoral Research Fellow to join the ACI’s Data Science research team and work on projects supporting the ACI’s Intelligent Cyber-Systems and Analytics Research Lab (ICSARL). The Fellow will be expected to take a leading role in developing, testing, and implementing generative machine learning (GML) to the cyber domain and its evolutionary properties. The closed world model of machine learning can fail catastrophically upon encountering the unknown. The successful candidate will explore open world recognition (OWR) for the cyber domain to enable cyber machine learning evolution within a rapidly changing environment. Within the context of the cyber domain, how do we anticipate newly emerging attack vectors and classes of data? How can we have proactive evolution of generated cyber data targeted towards adversarial behavior? The objective of this project is to investigate and develop GML techniques for out-of-distribution training data expansion in the network intrusion detection system (NIDS) setting, to include cyber adversarial behavior evolution. The Fellow will aim to generate evolutionary cyber machine learning data sets for OWR, as well as conduct temporal testing for evolution (injecting adversarial evolution through GML, cyber adversarial modeling, and subject-matter-expert input). Evolutionary computation, reinforcement learning, uncertainty quantification, and statistical computing methods will be explored for modeling and simulation to enable broad resilience. It is expected that the Fellow will be able to assist in the writing of scholarly manuscripts along with future research project white papers and proposals, making positive scholarly contributions that are of mutual interest with the Principal Investigator, and also productively interact with research collaborators within the ACI, across USMA, and with external partners.

Fields of Study:

  • Computer, Information, and Data Sciences
  • Mathematics and Statistics

Fellow Requirements:

  • US Citizen or Legal Permanent Resident
  • Ph.D. in data science, statistics, operations research, applied mathematics, artificial intelligence, cognitive science, computer science, decision science, information systems and technology, industrial and systems engineering, electrical engineering, computational science and engineering, computational social science, econometrics, quantitative economics, or related fields.
  • Proficiency in programming languages (Python, R, Julia, Matlab, etc.) along with modern software development practices, tools and technologies.
  • Knowledge of computer and network security principles, as well as knowledge of general cybersecurity data sets and tools.

Topics Relevant to this Posting:

Optimization; Simulation; Generative Methods; Bayesian Methods; Statistical Computing; Machine Learning; Deep Learning; Meta-learning; Adversarial Machine Learning; Robust Learning and Inference; Distributed Optimization and Learning; Evolutionary Computation; Game Theory; Unsupervised Learning, Reinforcement Learning, Multimodal Data Fusion and Generation; Intelligent Systems; Uncertainty Quantification; Decision-support Systems; Expert Systems.

Fellowship Educational Stipend Amount:

  • Total Stipend: up to $100,000 (Base educational stipend $90,000, Health Insurance Allowance up to $7,000 and Relocation Allowance up to $3,000)
  • Additional Research Travel Stipend

Other documents that Fellows need to submit with application:

  • Three references – only references names and contact information required
  • Writing sample (discipline related)

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