Data Analytics for Next-Generation 2D Semiconductor Devices

At imec, we
develop advanced electronic devices based on emerging 2D semiconductor
materials such as MoS₂, WSe₂, and WS₂. These technologies are being explored
for future low-power and high-performance electronics using device structures
ranging from MOS capacitors and transistors to Hall-bar test structures. A key challenge
is the efficient extraction of meaningful device parameters from the rapidly
growing volume of measurement data. To address this, we are developing a
Python-based analysis framework that automatically processes electrical
characterization data and extracts key figures of merit such as threshold
voltage, subthreshold swing, and mobility from two-probe transistor
measurements. Your Role The primary goal
of this internship is to extend this analysis framework to support a broader
range of characterization techniques and device structures, including:
Four-probe transistor
measurements
MOS capacitor (C-V)
characterization
Hall-bar measurements
New measurement platforms
and data formats You will develop
robust algorithms for automated parameter extraction, ensure compatibility
across different measurement tools, and help build a scalable software
framework that researchers can use across multiple projects and technologies. A smaller part of
the project will involve qualifying new characterization equipment and
validating its output against existing measurement platforms. What You Will Learn
Semiconductor device
physics and characterization
Electrical measurements on
advanced 2D-material devices
Scientific software
development in Python
Automated data analysis of
large experimental datasets Impact Your development will directly accelerate imec's research on next-generation
semiconductor technologies. By transforming large volumes of raw measurement
data into reliable device metrics, your work will enable researchers to
evaluate new devices faster, compare technologies more effectively, and gain
deeper insight into the underlying device physics. Type of internship : Bachelor internship, Master internship Duration : 6-9 months Required educational background : Computer Science, Electrotechnics/Electrical Engineering, Nanoscience & Nanotechnology, Physics University promotor : Devin Verreck (KULeuven) Supervising scientist(s) : For further information or for application, please contact Ward Janssens ( [email protected] ) and Kaustuv Banerjee ( [email protected] ) The reference code for this position is 2026-INT-353 . Mention this reference code in your application. Imec allowance will be provided. Applications should include the following information: resume motivation current study Incomplete applications will not be considered