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2023 PhD Graduate - Data Scientist

Johns Hopkins Applied Physics Lab

Job Description

Description

Are you passionate about employing innovative mathematical and statistical methodologies to solve important problems affecting the world we live in?

 

Does the prospect of engineering and improving data-driven solutions to national defense problems excite you?

 

We are seeking a motivated, hard-working physical data scientist to help us generate well-informed optimized solutions to problems in highly decentralized, heterogeneous environments! As part of our group, you will work with a core team of mathematicians, engineers, statisticians, and scientists to make meaningful and ground-breaking contributions in the interest of our national defense and security! We are a collaborative and hard-working team that strives to foster a culture of mentorship, growth and development, and thrives with the proposition of adapting creative and innovative methodologies to address exciting challenges and multi-disciplinary problems.

 

As a member of our team, you may…

  • Research, design and implement frameworks and optimization methodologies, for algorithm development and representation of decentralized combat system elements.
  • Conduct and enhance simulation and analysis of current and experimental system elements with an emphasis on command and control (C2) resilience.
  • Assess and advance efficacy, efficiency and adaptability of different models representing elements across multiple scales of fidelity,
  • Work on advanced data analytic and deep learning techniques to solve challenging problems in EW and/or maritime operations,
  • Leverage funding opportunities to focus on and shape direction of future research and development.
  • Work closely with domain and system experts to understand requirements, engineering concepts, and identify areas where surrogate modeling and statistical learning methods are appropriate for understanding system behavior.

Qualifications

You meet our minimum qualifications for the job if you...

 

  • Have a PhD degree in an Engineering field, or Applied Math, or Statistics, or Data Science, or Physics, or related.
  • Have research or internship experience, and are skilled in developing and/or analyzing dynamical system frameworks using an interpreted language or scientific computing tool such as MATLAB or Python. Or Tensorflow or PyTorch.
  • Have exposure to decision making under uncertainty, probability, stochastic processes or machine learning concepts or theories through classwork, internships, or thesis work.
  • Have knowledge/experience in Statistical processing, detection theory, estimation theory, tracking, radar signal processing, EO-IR sensing, passive sensing, multi-sensor and multi-modal sensor fusion,  Deep learning concepts (supervised, unsupervised, reinforcement learning, convolutional neural networks, recurrent neural networks, generative adversarial networks, etc...), deep Learning applicable to RF and EO-IR sensor data, advanced data analytic techniques, low dimensional signal processing techniques, communication theory, Probability and random processes.
  • Can demonstrate strong interpersonal skills and the ability to work independently and on a multi-disciplinary team.
  • Can demonstrate that you are fully vaccinated against COVID-19. To ensure the safety and well-being of the community, APL has established a policy requiring that all staff be vaccinated against COVID-19. All staff members must provide proof of full vaccination or have an approved medical or religious accommodation by their start date.
  • Are able to obtain Interim Secret level security clearance by your start date and can ultimately obtain Secret level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.


You'll go above and beyond our minimum requirements if you...

  • Have demonstrated skills in analyzing large-scale physical processes, using Monte Carlo simulation methods
  • Have knowledge of high-performance computing resources for large-scale parallel processing, and/or have experience developing surrogate representations of highly detailed physics-based systems.
  • Hold an active DoD Secret or TS/SCI Clearance.

 

Why work at APL?

The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation’s most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates.

 

At APL, we celebrate our differences and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL’s campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at www.jhuapl.edu/careers.


About Us

APL is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law.

 

APL is committed to promoting an innovative environment that embraces diversity, encourages creativity, and supports inclusion of new ideas. In doing so, we are committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contact Accommodations@jhuapl.edu. Only by ensuring that everyone’s voice is heard are we empowered to be bold, do great things, and make the world a better place.

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