Unknown Company

Doctoral candidate position (m/w/d) (DC6) Metrology on a wafer level (electrical/optical charac[...]

remote, oh • Posted 1 weeks ago
Onsite Contract Engineering

Organisation/Company Friedrich-Alexander University Erlangen-Nurnberg Department Materials Science Research Field Engineering » Materials engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 31 Aug 2026 - 12:00 (Europe/Berlin) Country Germany Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Dec 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Reference Number FAU-DC6 Marie Curie Grant Agreement Number Is the Job related to staff position within a Research Infrastructure? No

Offer Description

TheFriedrich-Alexander Universität Erlangen-Nürnberg (FAU) - Crystal Growth Lab (Materials Department 6) is seeking a highly motivated candidate for a PhD position (36 months) focused on Metrology on a wafer level (structural and morphologic characterization of 3C-SiCOI stacks).

This position is part of "Silicon carbide photonic integrated circuit (SiCPIC) ", a prestigious European Doctoral Network project funded by the European Union’sHorizon Europe Research and Innovation Programme under theMarie Skłodowska-Curie Action (MSCA), Grant Agreement No. .

  • International Collaboration: The PhD candidate will join aninternational team of 15 doctoral students acrossfive European countries , partnering with 5 universities and one company.
  • Research Focus: All 15 PhD projects fall under the project theme ofSilicon Carbide on Insulator (SiCOI) devices and integration for applications in classic and quantum optical telecommunication and optical sensing.

This PhD project will take place at FAU; additionally, the position includes mandatory international planned secondment and comprehensive training:

  • Freiberg Instruments, Freiberg (D) (2 months): Minority carrier lifetime measurements
  • CNRS, Grenoble (FR) (1 month): Ellipsometry
  • DTU, Lyngby (DK) (2 months): Optical characterization using waveguide structures
  • Training & Networking: The student will participate incommon meetings with the other 14 PhD students in the network, includingthree dedicated training schools

As a participant in the SiCPIC project, the PhD student will become part of a team at FAU in the Crystal Growth Lab (Materials Department 6), with expertise in crystal growth and characterization of semiconductor materials. The activities within the project will benefit from synergies with other projects in the group as well as with other activities at the institute. The main supervisor will be Professor Peter Wellmann, FAU.

Excellent master's degree in materials science, nanotechnology, electrical engineering, physics, or a comparable field / Good written and spoken English skills / Ability to work independently and as part of an interdisciplinary team / Positive attitude, enjoyment of research, and finding new solutions.

In the EU project SiCPiC the so-called CVD (Chemical Vapor Deposition) and CS-PVT (Close-Space Physical-Vapor-Transport) processes are investigated with regard to their use in new photonic applications of SiC. The tasks of the three doctoral candidate (DC3,5,6) positions at the Crystal Growth Lab at FAU CGL include SiC layer fabrication, surface preparation and electrical-optical characterisation. ML/AI assisted methods support the experiment planning and analysis. It is expected that all three doctoral candidates collaborate together beyond their own research focus. Each of the three doctoral candidate positions focus on one of the three tasks: DC6 focusses on Metrology on a wafer level (focus on electrical/optical characterization) and ML/AI assisted data anlysis .

Due to restrictive legal requirements for technology export control, project staff must be citizens of the European Union, Switzerland, Norway, Island, Japan or the USA/Canada/Australia/New Zeeland.

Specific Requirements

Preliminary knowledge in the field of materials characterization of semiconductors and ML/AI assisted data analysis are an advantage.

#J-18808-Ljbffr
Back to Job Search