2022 Summer Research Intern - Exploratory Physical Sciences
Introduction
At IBM, work is more than a job – it’s a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you’ve never thought possible. Are you ready to lead in this new era of technology and solve some of the world’s most challenging problems? If so, lets talk.
Your Role and Responsibilities
Start and end dates for this Internship are during Summer 2022 (3 months) at IBM Research. At IBM Research, we invent things that matter to the world. Today, we are pioneering the most promising and disruptive technologies that will transform industries and society, including the future of Hybrid Cloud, AI, and Quantum Computing. And looking to the horizon, we are placing big bets on a pipeline of ambitious exploratory science breakthroughs which will be foundational for the future of computing. We are driven to discover. With more than 3,000 researchers in 12 labs located across six continents, IBM Research is one of the world’s largest and most influential corporate research labs.
The Exploratory Physical Sciences program at IBM Research is seeking candidates who will contribute to foundational research topics in Applied Physics and Material Science. Currently, positions are open to 2 distinct areas: Topological Materials for Information Technology and Physically Constrained Data-Driven AI.
Candidates should possess one or more of the following:
- A background in Physics, Material Sciences, Electrical Engineering or Chemical Engineering
- Track record of co-authoring technical reports and publications
- Programming experience in scientific computing
- Requirements for Topological Materials for Information Technology:
- Experimental experience in conducting research in solid state physics
- Experience performing transport measurements: electrical, magneto-transport, optomagneto-transport
- Experience with cryogenic/variable-temperature experiments
- Knowledge about device fabrication and layout design
- Preferred: Knowledge in topological materials, quantum transport physics, and semiconductor physics
- Requirements for Physically Constrained Data-Driven AI:
- Experience with development of detailed spectral models incorporating the effects of atmospheric effects including molecules, clouds and aerosols, covering spectral range from the microwave to the ultraviolet
- Detailed spectral validation of these models against atmospheric data
- The development of radiatively consistent, computationally efficient radiative transfer models for remote sensing images and climate models
At this time, an in-person program is planned, and candidates would need to work in the IBM Research Center in Yorktown Heights, NY.
The World is Our Laboratory: No matter where discovery takes place, IBM researchers push the boundaries of science, technology, and business to make the world work better. IBM Research is a global community of forward-thinkers working towards a common goal: progress.
Required Technical and Professional Expertise
Candidates should possess one or more of the following:
- Candidates should possess an undergraduate degree in Physics, Material Sciences, Electrical Engineering or Chemical Engineering, and be pursuing a graduate degree in same
- Track record of co-authoring technical reports and publications Requirements for Topological Materials for Information Technology:
- Experimental experience in conducting research in solid state physics
- Experience performing transport measurements: electrical, magneto-transport, optomagneto-transport
- Experience with cryogenic/variable-temperature experiments
- Knowledge about device fabrication and layout design
- Preferred: Knowledge in topological materials, quantum transport physics, and semiconductor physics
- Requirements for Physically Constrained Data-Driven AI:
- Experience with development of detailed spectral models incorporating the effects of atmospheric effects including molecules, clouds and aerosols, covering spectral range from the microwave to the ultraviolet
- Detailed spectral validation of these models against atmospheric data
- The development of radiatively consistent, computationally efficient radiative transfer models for remote sensing images and climate models
Preferred Technical and Professional Expertise
- Programming experience in scientific computing, computational math, and/or high-performance computing.
- Ph.D. candidate