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Python using modern ML libraries (e.g., PyTorch / TensorFlow) and common scientific tooling. Demonstrated ability to communicate technical results clearly in written deliverables and presentations. Ability
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on Azure/AWS managed VMs). Experience with container storage, cloud storage (AWS S3, Azure Blob), monitoring and capacity planning tools, automation (PowerShell, Python, Ansible), and operational tooling
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++). High-level programming languages (e.g. Java, Python, GoLang, etc.) Software engineering and design concepts Firmware and device driver development Malware tradecraft and threat actor tactics, techniques
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research and applying scientific methods. Mastery of C/C++, Python, Verilog/VHDL, and/or other pertinent languages and software tools and frameworks. Experience leading research projects and collaborating
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and organizational skills If coming from a computing background: strong programming skills (e.g., Python/C++), ideally with experience in one or more of the areas in the tracks above If coming from a
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, background in neuroscience. Candidates should have prior experience with electrophysiology, behavioral analysis, and stereotaxic surgery. Additional experience in computational methods and programming (Python
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++, Python), and data analysis. Familiarity with ultrasound imaging and medical signal analysis is highly desirable. Excellent written and oral communication skills, and the ability to work collaboratively in
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: Bachelor's Degree in Computer Science, Computer Engineering, AI or a related field. Experience with Python programming and Deep Learning frameworks (PyTorch). Experience with Large Language Models (LLMs) and
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software developer, software engineer, or verification engineer. You understand the Department of War (DOW) Systems Engineering lifecycle. You’re proficient in one or more of the following: C and C++, Python
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understanding of AI/ML Basic proficiency with a programming language (preferably Python) Familiarity with common AI/ML software packages and tools (e.g. Pytorch, TensorFlow, ART) Ability to collaborate internally