Asir Intisar Khan

We are always excited to welcome energetic and motivated researchers, including Postdocs, Ph.D. and Master's students, and Undergraduates to our group. We value individuals who share our research vision and bring relevant expertise, as well as those who contribute fresh perspectives, new skills, and innovative ideas that strengthen and expand our scientific efforts.

Postdoctoral Researchers: We are seeking outstanding and highly motivated postdoctoral candidates with deep expertise in one or more of the following areas:

(i) Nano and micro-scale thermal management and nanofabrication, (ii) Nanofabrication and characterization of emerging memory devices, (iii) Synthesis, transport, and modeling of topological materials, (iv) Modeling and architecture of heterogeneous memory systems for AI, (v) Physics-based and/or AI/ML modeling and/or AI/ML optimization for topics (i-iv)

To apply: Interested applicants should send a PDF copy of their CV along with a brief statement of research alignment in the body of an email (asir@berkeley.edu) to me. Additionally, a 1-page cover letter as a PDF attachment describing relevant experience, research alignment, and interest is highly encouraged but not required.

Keep the subject line concise and specific (e.g., Postdoc Application – AI Hardware). Ensure the email body is focused, thoughtful, and clearly outlines your relevant expertise and how it aligns with one or more of the focus areas listed above.

Graduate Students: Our group is looking to welcome 3-4 new Ph.D. students each year, with openings starting as early as Spring (Jan) 2026. We welcome applicants from a range of disciplines, including Electrical Engineering, Materials Science, Mechanical Engineering, Physics (or Applied Physics), Computer Engineering, Chemical Engineering, and Chemistry. If our research matches your interests and expertise, we would like to encourage you to reach out. See the Areas of Interest below.

To apply: In your email, start the subject line with: “Prospective PhD Applicant”. Briefly describe what you would like to work on, and explain how you would extend or improve on one of the areas of your interest that aligns with us. Attach your CV as a PDF. If you’ve worked with any of our collaborators or have relevant industry or research experience, mention that in your email as well.

If you are applying to EECS in Fall, please select “Asir Intisar Khan” as one of your top faculty of interest during the Fall PhD application cycle. If you are applying through a non-EECS program, please mention my name in your Statement of Purpose, and email me to let me know what department you are applying to.

Master's students and Undergraduates: We welcome Master’s and Undergraduate students currently at UC Berkeley who are enthusiastic about our research and willing to commit time and effort toward impactful projects.

To apply: If you are interested in joining our group, please email me at asir@berkeley.edu with the subject line Research Interest – [Undergraduate/Master’s] – [Your Name]. Briefly describe your background, research interests, and why you are interested in our work. Attach your CV (PDF), mention any relevant coursework or experience, and, if possible, refer to one or more of our recent papers or research areas that align with your interests. We are particularly interested in leveraging AI/ML for accelerated design of experiments, materials discovery, and physics-informed modeling, to enhance our understanding and optimization of materials and devices at multiple scales.

We are always looking for motivated, curious students who are committed to meaningful research; opportunities should be available during the academic year and/or summer.

Areas of Interest:

(i) Nano and micro-scale heat transfer, thermal characterization, heat management, and nanofabrication, (ii) Nanofabrication and characterization of emerging memory devices, (iii) Ferroelectric heterostructure deposition, metrology, and transport characterization. (iv) Synthesis, electronic transport, and theoretical modeling of topological materials. (v) Physics-based and/or AI/ML modeling and/or AI/ML optimization for topics (i-v);

Our group will focus on the development of low-power electronic devices by engineering heterogeneous device platforms and transformative materials, with a particular emphasis on controlling charge, heat, and spin transport at their interfaces. We are especially excited to contribute to next-generation AI hardware on both rigid and flexible substrates, and to explore novel interconnects and new thermal strategies for energy-efficient, 3D-integrated electronic systems. We are also interested in leveraging machine learning for accelerated design of experiments, materials discovery, and physics-informed modeling, to enhance our understanding and optimization of materials and devices at multiple scales. These efforts and innovations will complement software and circuit design efforts, driving collaboration and multiplying energy-efficiency gains across computing hardware.

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