Summary
Lund University, a top-ranked institution, is seeking a highly motivated Postdoctoral Researcher to join the Division of Solid State Physics at the Department of Physics. This position focuses on developing data-driven approaches, combining machine learning with physics-based understanding, to optimize the growth of semiconductor materials. The successful candidate will contribute to a large initiative aimed at achieving deterministic control of atomic configurations in ultra-wide bandgap (UWBG) materials like AlN, crucial for next-generation energy technologies. The role involves developing machine learning methods, analyzing experimental data, and identifying optimal growth parameters within a collaborative, interdisciplinary research environment.
Designation
Postdoctoral Researcher
Research Area
- Machine Learning for Materials Science
- Data-driven Optimization of Semiconductor Material Growth
- Ultra-wide Bandgap (UWBG) Semiconductors (e.g., AlN)
- Solid State Physics
- Nanoscience and Nanotechnology
Location
Division of Solid State Physics, Department of Physics, Lund University, Lund, Sweden
Eligibility/Qualification
Required Qualifications:
- A PhD or an international degree equivalent to a PhD in physics, materials science, or an equivalent field, with specialization in machine learning and data-driven approaches.
- Priority given to candidates who graduated no more than three years ago before the last day for application (special circumstances may allow for earlier graduation).
- Very good oral and written proficiency in English.
- Experience in modeling of multiphase systems (e.g., liquid/solid, gas/liquid, liquid/liquid, or gas/solid).
- Experience in the application of machine learning approaches.
- Experience in scientific computing for experimental data analysis.
Desirable Qualifications:
- Knowledge of semiconductor physics.
- Knowledge of ultrawide bandgap semiconductors.
- Proven experience in writing scientific papers.
- Teaching skills (up to 20% of working hours may include teaching).
Job Description
The main duties of this postdoctoral position are primarily research-focused, with the opportunity for up to 20% teaching. The position aims to foster the researcher’s independence and professional development. Key research tasks include:
- Developing machine-learning methods using experimental data provided by collaborating experimentalists.
- Identifying and defining the most relevant parameters governing material growth based on underlying physics.
- Developing an open-source computational framework for analyzing experimental data.
- Identifying relationships between growth conditions and material properties.
- Proposing optimized growth parameters for semiconductor materials.
The research will be conducted in close collaboration with PhD students and researchers within the competence center for III-Nitride technology C3NiT, a European network within the WBG Pilot Line, and experienced researchers in materials growth and characterization at the departments of solid state physics and synchrotron radiation physics. This is a full-time, fixed-term employment for 3 years.
How to Apply
Applications must be submitted via Lund University’s recruitment system. The application should include:
- A comprehensive CV.
- A personal letter justifying your interest in the position and detailing how your qualifications match the requirements.
- A degree certificate or equivalent.
- Any other relevant documents you wish to highlight (e.g., copies of grade transcripts, details of referees, letters of recommendation).
Last Date for Apply
Until position filled
Apply Link
https://lu.varbi.com/en/what:job/jobID:967223/type:job/where:4/apply:1
