Postdoctoral Scholar – AI-Assisted Physical Vapor Deposition of Thin Films

Lawrence Berkeley National Laboratory • Berkeley, CA

13d • Onsite

About The Position

Lawrence Berkeley National Laboratory is hiring a Postdoctoral Scholar – AI-Assisted Physical Vapor Deposition of Thin Films within the Molecular Foundry Division. This position will accelerate process development and exploration of nonlinear optical and superconducting materials heterostructures. The postdoc will be part of a collaborative team of researchers in the Molecular Foundry from the Inorganic Nanostructures, Data Science and Infrastructure, Imaging and Manipulation, and nanofabrication facilities. The postdoc will create thin film heterostructures combining nonlinear optical materials and superconductors and other functional and passivation layers essential for realization of quantum transducers.
Novel materials in thin-film form are essential to the progress of quantum technologies. Thin-film synthesis of nonlinear optical materials with high χ2 coefficients of particular interest as it will enable fabrication of quantum transducers. These are devices that enable controlled conversion of signal or excitation from one physical carrier to another and combine photonic and superconducting circuits in a monolithic device. The Molecular Foundry has acquired recently thin film deposition cluster tools aimed at synthesis of thin film materials stacks to enable integration of new functional layers in quantum devices. Of particular interest is integration of Lithium Niobate or other high χ2 material with superconductors. We are looking for a researcher with experience developing synthetic protocols using reactive sputtering and pulsed laser deposition and relevant materials and thin film characterization techniques.

Requirements

• Recent Ph.D. (within the last 3 years) in Physics, Chemistry, Material Science or a closely related field.
• Demonstrated background in experimental research including collaborating on projects from initiation to conclusion, demonstrating creative problem-solving abilities.
• Experience in any combination of the following areas: Physical and chemical deposition of thin films (e.g. reactive sputtering, Pulsed laser deposition, ALD, e-beam evaporation, etc.)
• Thin film characterization (e.g. x-ray diffractometry, optical microscopy, XPS, optical spectroscopy)
• Analytical electron microscopy (TEM, STEM, EELS, etc.)
• Nonlinear optical materials property measurements
• Process development and optimization (nanofabrication and/or materials deposition)
• Strong organizational skills including the ability to prioritize work, meet deadlines, and contribute to the planning of a scientific research program.
• Excellent oral and written communication skills including the ability to organize technical/scientific information, write manuscripts, and present at conferences.
• Strong teamwork and interpersonal skills including the ability to collaborate with a diverse interdisciplinary research team.

Nice To Haves

• Knowledge of photonic and/or superconducting materials and devices
• Experience with electron based spectroscopic techniques such as EELS, EDS or Cathodoluminescence.
• Background knowledge in materials or low temperature physics.
• Demonstrated knowledge of Python or another major programming language for data analysis and familiarity with machine learning approaches for data analysis.

Responsibilities

• Develop materials and/or fabrication processes for phononic and superconducting devices including details materials/device characterization
• Collaborate with Foundry scientists on material development and tailoring of interfacial properties.
• Present research results at national conferences and author publications.
• Provide research support, assistance and instruction to other team members as needed.
• Foster a culture of safety and actively promote diversity, equity and inclusion.
• Adhere to DOE and Berkeley Lab’s safety guidelines and safety culture, and contribute to an inclusive and supportive work environment for all.

What This Job Offers

• Job Type: Full-time
• Education Level: Ph.D. or professional degree
• Number of Employees: 11-50 employees