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Data Analytics for Next-Generation 2D Semiconductor Devices

Stage 25 tot 36 maanden

Leuven (Belgium)

Gepubliceerd op 20 oktober 2026

  • Contract

    Stage 25 tot 36 maanden

  • Locatie

    Leuven (Belgium)

  • Startdatum

    Zo snel mogelijk

  • Loon

    Informatie niet verstrekt

  • Thuiswerken

    Niet gespecificeerd

At imec, wedevelop advanced electronic devices based on emerging 2D semiconductormaterials such as MoS₂, WSe₂, and WS₂. These technologies are being exploredfor future low-power and high-performance electronics using device structuresranging from MOS capacitors and transistors to Hall-bar test structures.

A key challengeis the efficient extraction of meaningful device parameters from the rapidlygrowing volume of measurement data. To address this, we are developing aPython-based analysis framework that automatically processes electricalcharacterization data and extracts key figures of merit such as thresholdvoltage, subthreshold swing, and mobility from two-probe transistormeasurements.

Your Role

The primary goalof this internship is to extend this analysis framework to support a broaderrange 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 developrobust algorithms for automated parameter extraction, ensure compatibilityacross different measurement tools, and help build a scalable softwareframework that researchers can use across multiple projects and technologies.

A smaller part ofthe project will involve qualifying new characterization equipment andvalidating 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-generationsemiconductor technologies. By transforming large volumes of raw measurementdata into reliable device metrics, your work will enable researchers toevaluate new devices faster, compare technologies more effectively, and gaindeeper 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 (< e-mail verwijderd om veiligheidsredenen >) and Kaustuv Banerjee (< e-mail verwijderd om veiligheidsredenen >)

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.

Uiterste sollicitatiedatum

Zolang de vacature online is

Opleidingsniveau

Bachelor-niveau of gelijkwaardig

Jobdomeinen

Statistiek, Data-analyse & Toegepaste Wiskunde

Meer informatie over het bedrijf

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