Summer Undergraduate Research Internships in Quantum Nanoelectronics & 2D Materials

Duration: 2–3 months (May–July 2026)
Location: Quantum Nanoelectronics & Devices Laboratory, Department of Physics, IISc Bangalore

We invite motivated undergraduate students to work on problems in quantum nanoelectronics, 2D materials, and scientific instrumentation. Projects span hands-on nanofabrication and optics, computational modeling of quantum electronic systems, machine learning for scientific imaging, and lab software/tool development. Students will work closely with PhD researchers and gain exposure to modern condensed-matter experiments and workflows.

Project Track A – Experimental Nanofabrication & Characterization

A1. Dry-Transfer Yield Optimization for van der Waals Heterostructures

Optimize dry-transfer processes for assembling 2D heterostructures (graphene, hBN, WSe₂). Includes exfoliation, controlled stamping, and defect inspection using optical microscopy.

You will learn: van der Waals assembly, optical inspection, practical process optimization.

A2. Low-Frequency Noise in Graphene Field-Effect Transistors

Measure 1/f noise in graphene devices under electrostatic control using lock-in instrumentation and spectral analysis.

You will learn: transport measurement techniques, low-noise electronics, MATLAB/Python analysis.

A3. Reflection Microscopy for Bubble & Wrinkle Mapping in 2D Stacks

Develop reflection microscopy workflows (including NIR illumination) to identify interfacial bubbles, wrinkles, and grain boundaries in stacked 2D materials.

You will learn: optical alignment, imaging, materials metrology, image-based defect grading.

A4. AFM-Assisted Graphene Cutting & Local Oxidation Lithography

Perform nanoscale patterning of graphene using AFM-based cutting and local anodic oxidation (LAO) techniques.

You will learn: scanning probe methods, nanoscale lithography, instrumentation alignment.

Project Track B – Theory & Computational Modeling

B1. Landau Level Modeling in ABA Trilayer Graphene

Simulate Landau level spectra in ABA trilayer graphene under displacement fields with a focus on gully formation.

You will learn: Hamiltonian modeling, numerical diagonalization, spectral visualization.

B2. Moiré Miniband Formation in BLG/hBN Superlattices

Compute minibands using k+G basis methods and analyze density-of-states features in bilayer graphene/hBN moiré systems.

You will learn: moiré physics, reciprocal-space modeling, DOS analysis.

B3. Quantum Capacitance of Graphene with Disorder Broadening

Model C–V characteristics of graphene under magnetic fields, incorporating Landau level broadening and screening.

You will learn: DOS modeling, numerical integration, links to real capacitance measurements.

B4. Cyclotron Focusing & Edge Collimation in 2D Electron Systems

Simulate classical trajectories in magnetic fields to study cyclotron focusing and edge skipping orbits.

You will learn: computational dynamics, visualization, intuitive QH edge physics.

Project Track C – Machine Learning & Computer Vision for the Lab

C1. ML Classification of Exfoliated Flakes

Build ML models to classify flake thickness from optical images of graphene, hBN, and WSe₂.

You will learn: dataset construction, CNN training, scientific image preprocessing.

C2. Automated Feature Extraction from Hall-Bar Device Images

Use computer vision to detect contacts, channels, and alignment marks from microscope images for documentation and simulation.

You will learn: OpenCV pipelines, segmentation/detection, scientific tooling.

C3. Bubble & Wrinkle Segmentation in van der Waals Stacks

Quantify stack cleanliness by segmenting and statistically characterizing bubbles and wrinkles in optical images.

You will learn: thresholding/clustering, defect metrics, materials-focused data science.

D1. Lock-In Based Data Acquisition & Visualization Toolkit

Develop Python/MATLAB tools for automated scans and real-time visualization during transport experiments.

You will learn: instrument control (e.g. PyVISA), DAQ automation, user-facing plotting/UX.

Who Can Apply?

  • Undergraduate students in Physics, EE/ECE/ME, Materials, or related disciplines
  • Comfortable with at least one of: lab work, coding, or data analysis
  • Able to commit full-time for 2–3 months (in-person, on campus)

Application Instructions

Please combine the following into a single PDF:

  • Short CV (max 2 pages)
  • Unofficial transcript / grade sheet
  • Statement of interest (max 1 page) indicating:
    • Your background and skills
    • Your top 3 preferred projects (e.g. A1, B4, C1)
    • Any prior research or project experience

Email: aveek@iisc.ac.in

Use the following subject line:

Application – Summer Research 2026 – <Your Name>

Application Deadline: 28 February 2026
Shortlisted candidates may be invited for a brief online discussion.

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