PhD Intern - Detection Physics at Pacific Northwest National Laboratory Job Richland area,Washington USA,Research/Development

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At PNNL,our core capabilities are dividedamongmajor departments that werefer to as Directorates within the Lab,focused on a specific area of scientific research orother function, with its own leadership teamand dedicated budget.

Our Science & Technologydirectoratesinclude National Security,Earthand Biological Sciences, Physical and Computational Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory,a Department of Energy, Office of Science user facility housed on the PNNL campus.

The National Security Directorate (NSD) drives science-based, mission-focused solutions to take on complex,real-world threats to our nation and the world.

The Nuclear, Chemical, and Biological Technologies Division, within the National Security Directorate, works across fundamental science, research and development, and operations to counter emerging national security threats. We focus on discovering signatures and understanding threats by creating materials, methods, and technologies to detect and analyze them. Our researchers deliver the solutions necessary for addressing complex mission challenges, such as explosives detection, biological threat detection, chemical and nuclear forensics, and special nuclear materials.

Responsibilities

PNNL is seeking graduate level interns with a background in software analysis to support a primarily R&D focused program spanning large-scale simulation, device emulation, software analysis, and remediation. This role blends hands-on development with deep technical evaluation and offers the opportunity to contribute to technical writing and publication.

Seeking an intern to support scientific research in the broad area of data science, machine intelligence and autonomous learning and reasoning. A successful candidate should have expertise in one or more of the following technical areas: optimization and optimization-based decision making, artificial intelligence and machine learning, and data analytics applied to modeling, diagnostics and control of cyber-physical systems, uncertainty quantification, system identification and model reduction, dynamical systems modeling and simulation, model predictive control, reinforcement learning algorithms, autonomous control and decision systems, and multi-agent systems.

Specific research is required to expand library capability across other domains and content types (including text, video and audio content) including collaborative research in the continued development of the Python library.

Example tasks include:

Research to expand library capability across other domains and content types (including text, video and audio content) Collaborative research in the continued development of the Python library
Prepare data sets for model training
Test deep learning models to obtain accuracy Research deep learning topics

Intern will be asked to contribute to project deliverables including contributing to monthly reports using the standard report template and to participate in weekly teleconferences as scheduled by the PNNL PM/PI.

Minimum Qualifications

Candidates must be currently enrolled/matriculated in a PhD program at an accredited college.
Minimum GPA of 3.0 is required.

Preferred Qualifications

Experience with one or more disassemblers (IDA, Binary Ninja, Ghidra)
Experience with one or more assembly languages (x86, ARM, RISCV, etc)
Comfortable with software development in compiled and scripting languages (C, C++, Rust, Python, etc)
Experience with object files, compilers, linkers, and loaders (ELF, DWARF, GDB, LLVM)
Experience with both static and dynamic program analysis techniques
Experience with reverse…