Postdoctoral Research Associate
$85.3kJohns Hopkins University Applied Physics Lab
Description
Are you passionate about pioneering advancements in additive manufacturing through cutting-edge sensing technologies, data fusion, and real-time control? Do you want to contribute to critical national challenges by enabling intelligent closed-loop monitoring and control of metal additive manufacturing processes? If so, we invite you to join our innovative research team in the Research and Exploratory Development Department (REDD) at the Johns Hopkins University Applied Physics Laboratory (JHU/APL). As an In-Situ Sensing Postdoctoral Fellow, you will be at the forefront of developing and integrating novel sensing modalities, artificial intelligence (AI), and machine learning (ML) algorithms to enhance process control, optimize material properties, and ensure the reliability of additively manufactured components. Your work will be essential in designing closed-loop control systems that adapt dynamically to real-time process data, enabling unprecedented advancements in manufacturing precision and efficiency. Our team is actively developing next-generation sensing and control solutions that will allow real-time adjustments to critical additive manufacturing parameters, such as laser power, scan speed, and material feed rate. By leveraging multi-modal sensor data-including optical, thermal, acoustic, and X-ray imaging-you will help to create intelligent feedback systems capable of identifying defects, predicting failure points, and optimizing manufacturing conditions. These advances will not only push the limits of metal additive manufacturing but will also enable new applications in mission-critical environments where reliability is paramount. As an In-Situ Sensing Postdoctoral Fellow, you will...- Collaborate with APL scientists, engineers, and technicians to develop novel closed-loop sensing and control solutions tailored for additive manufacturing.
- Perform pioneering research in materials and process characterization by fusing in-situ sensing modalities to optimize microstructure and density in metal additive manufacturing.
- Utilize AI and ML algorithms to extract insights from multi-modal sensor data, improve real-time process monitoring, and drive automated control systems.
- Design, implement, and validate adaptive control algorithms that leverage sensor feedback to dynamically adjust processing parameters in real time.
- Engage with a multidisciplinary team focused on materials discovery, novel fabrication techniques, multiscale modeling, processing insights, advanced testing, and qualification science.
- Present technical findings to both internal and external audiences, effectively communicating complex concepts to team members, task leads, and project leadership.
- Contribute to the design, fabrication, and characterization of additively manufactured operational prototypes that demonstrate intelligent process control.
- Possess a Ph.D. in Mechanical Engineering, Electrical Engineering, Materials Science, Data Science, or a related field.
- Have strong written and oral communication skills, with the ability to engage wide - ranging audiences and adapt to different communication styles.
- Are adaptable, enthusiastic about new challenges, and have a passion for learning with a collaborative mindset open to sharing and receiving feedback.
- Have experience solving multidisciplinary research challenges related to qualified hardware and additive manufacturing.
- Demonstrate a fundamental understanding of additive manufacturing, including process defects, microstructure evolution, and thermodynamic solidification.
- Have a demonstrated track record of authoring research proposals and publishing high-impact journal papers.
- Are willing and able to work in a laboratory setting and travel for field testing, sponsor meetings, conferences, and technical presentations.
- Are able to obtain a Secret-level security clearance to start with APL and then upi will be required to obtain a final Top Secret clearance. If selected, you will be subject to a government security clearance investigation, and must meet the eligibility requirements for access to classified information, including U.S. citizenship.
- Have experience fielding additively manufactured components.
- Demonstrate the ability to fuse 2D and 3D data, including in-situ and post-manufacturing data, into a 3D format for advanced processing and visualization.
- Have experience applying AI/ML techniques to complex datasets, including deep learning models for defect detection, anomaly detection, and predictive modeling of additive manufacturing processes.
- Have hands-on expertise in developing novel in-situ monitoring methods for additive manufacturing, including custom sensor development to improve signal-to-noise ratios and spatial registration.
- Have experience with digital twin technology and reinforcement learning for real-time optimization of manufacturing parameters.
- Have experience working with voxel-based data and mapping physical quantifications across multiple sensing platforms.
- Possess strong scientific programming skills using tools such as MATLAB or Python, with experience in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
At APL, we encourage our team members to generate and lead their own research initiatives while also publishing their findings in high-impact venues. We are a collaborative, risk-taking, and innovative research team dedicated to solving complex technical challenges with national impact. If you are excited about the opportunity to shape the future of additive manufacturing through sensing, AI, and adaptive control systems, we would love to hear from you!
About Us 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 of perspectives 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 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 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 [email protected]. The referenced pay range is based on JHU APL's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and/or contractual designation. Additional compensation may be provided in the form of a sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis.
Minimum Rate $85,300 Annually
Maximum Rate $155,500 Annually
Vacancy posted 13 hours ago
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