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Master thesis: Inverse design of nanophotonic through generative deep learning models(m/w/x)
Description
In this role, you will engage in cutting-edge research, developing and optimizing machine learning models for nanophotonics. Your responsibilities include reviewing literature, enhancing model performance, and documenting findings to contribute to innovative imaging systems.
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Upload your CV and Nejo AI will find matching job offers for you.
Requirements
- •Strong background in machine learning and deep learning techniques
- •Enrollment in a Master's program in computer science, electrical engineering, mechanical engineering, optics and photonics, or a comparable field
- •Familiarity with generative models
- •Enjoyment of learning about new topics and contributing ideas
Education
Tasks
- •Conduct a literature review on machine learning libraries and frameworks
- •Research and develop machine learning models for nanophotonic inverse design
- •Optimize and evaluate model performance for real-world applications
- •Document algorithms developed and results
Languages
English – Business Fluent
Benefits
Parking & Commuter Benefits
- •Good public transport connections
Informal Culture
- •Open and collegial working atmosphere
Other Benefits
- •Intensive support
- •Diversity promotion
Flexible Working
- •Opportunity to work remotely
Purpose-Driven Work
- •High degree of personal responsibility
- •Opportunity to contribute and implement own ideas
- Fraunhofer-GesellschaftFull-timeWith HomeofficeNot specifiedKarlsruhe
- Fraunhofer-Gesellschaft
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Master thesis: Inverse design of nanophotonic through generative deep learning models(m/w/x)
The AI Job Search Engine
Description
In this role, you will engage in cutting-edge research, developing and optimizing machine learning models for nanophotonics. Your responsibilities include reviewing literature, enhancing model performance, and documenting findings to contribute to innovative imaging systems.
Let AI find the perfect jobs for you!
Upload your CV and Nejo AI will find matching job offers for you.
Requirements
- •Strong background in machine learning and deep learning techniques
- •Enrollment in a Master's program in computer science, electrical engineering, mechanical engineering, optics and photonics, or a comparable field
- •Familiarity with generative models
- •Enjoyment of learning about new topics and contributing ideas
Education
Tasks
- •Conduct a literature review on machine learning libraries and frameworks
- •Research and develop machine learning models for nanophotonic inverse design
- •Optimize and evaluate model performance for real-world applications
- •Document algorithms developed and results
Languages
English – Business Fluent
Benefits
Parking & Commuter Benefits
- •Good public transport connections
Informal Culture
- •Open and collegial working atmosphere
Other Benefits
- •Intensive support
- •Diversity promotion
Flexible Working
- •Opportunity to work remotely
Purpose-Driven Work
- •High degree of personal responsibility
- •Opportunity to contribute and implement own ideas
About the Company
Fraunhofer-Gesellschaft
Industry
Research
Description
Das Unternehmen ist eine der führenden Organisationen für anwendungsorientierte Forschung mit 76 Instituten in Deutschland.
- Fraunhofer-Gesellschaft
Masterarbeit: Inverses Design von Nanophotonik durch generative Deep-Learning-Modelle(m/w/x)
Full-timeWith HomeofficeNot specifiedKarlsruhe - Fraunhofer-Gesellschaft
Master thesis: Simulation and design for metasurface polarization optics(m/w/x)
Full-timeWorking StudentWith HomeofficeKarlsruhe - Fraunhofer-Gesellschaft
Masterarbeit: Simulation und Design von Metasurfaces für Polarisationsoptik(m/w/x)
Full-timeWith HomeofficeNot specifiedKarlsruhe - Fraunhofer-Gesellschaft
Masterarbeit - Renderingbasierte 3D-Rekonstruktion aus Satellitenbildern mit Deep Learning(m/w/x)
Full-timeInternshipWith HomeofficeEttlingen - Fraunhofer-Gesellschaft
Abschlussarbeit: Realistische Simulation von Event-Streams mittels digitalem Zwilling(m/w/x)
Full-timeInternshipWith HomeofficeKarlsruhe