Master Thesis Deep Learning for Ultrasound

Robert Bosch Group; Renningen; Vor Ort; EUR 40.000 - 60.000; Vollzeit

Zusammenfassung

A leading technology company in Germany offers a Master Thesis opportunity focusing on developing deep learning models for ultrasound. Candidates should have a Master's in Engineering or Natural Sciences with excellent grades and strong skills in Deep Learning and Computer Vision. The role provides practical experience and collaboration in innovative projects.

Qualifikationen

• Strong knowledge and practical experience in Deep Learning and Computer Vision.
• Must excel at working independently and be intrinsically motivated.
• Very good grades in relevant Master studies required.

Aufgaben

• Develop and implement innovative deep learning models for ultrasound data.
• Fuse ultrasound data with video data for enhanced performance.
• Evaluate and compare new models against baseline models.
• Work with real-world data for practical and robust solutions.

Kenntnisse

Deep Learning

Computer Vision

Machine Learning

3D perception systems

Python

PyTorch

Ausbildung

Master studies in Natural Sciences or Engineering

Jobbeschreibung

Master Thesis Deep Learning for Ultrasound

• Full-time

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other.

Join in and feel the difference.

TheRobert Bosch GmbHis looking forward to your application!

Automated parking in challenging scenarios requires a precise free space estimation. Ultrasound sensors are suitable for high-precision predictions in close range. The topic of the thesis is the development of deep learning models for ultrasound, which exhibit good performance and are computational efficient.

Responsibilities

• Develop and implement innovative ideas and new deep learning models for ultrasound data.
• Fuse ultrasound data with video data and process them together to enhance performance.
• Evaluate and compare new models to existing baseline models.
• Work with real world data to ensure practicality and robustness of solutions.

Qualifications

• Education: Master studies in Natural Sciences or Engineering (Machine Learning, Computer Science, Math, Statistics, Physics, Cybernetics, Electrical/Mechanical Engineering) with very good grades.
• Experience and Knowledge: strong knowledge and practical experience in Deep Learning, Computer Vision, Machine Learning, and 3D perception systems; Python and deep learning framework (preferably PyTorch).
• Personality and Working Practice: excel at working independently and strongly intrinsically motivated.

Start: according to prior agreement
Duration: 6 months

Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.

Need further information about the job?
Kilian Rambach (Functional Department)
[phone]