Students : Exploring Machine Learning Applications in Real-Time Dose Verification for Proton Therapy

Fraunhofer-Gesellschaft; Chemnitz; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

Ein innovatives Forschungsinstitut sucht leidenschaftliche Studierende für Masterarbeiten, Praktika und studentische Hilfskräfte. Diese spannende Gelegenheit bietet die Möglichkeit, an der Schnittstelle von Gesundheitswesen, Technologie und Datenwissenschaft zu arbeiten. Sie werden Teil eines internationalen Expertenteams, das an realen Anwendungen in der Halbleiterfertigung und Medizintechnik arbeitet. Wenn Sie praktische Erfahrung mit AI und Machine Learning haben und interdisziplinär arbeiten möchten, ist dies die perfekte Chance für Sie, Ihre Fähigkeiten in einem dynamischen Umfeld weiterzuentwickeln.

Qualifikationen

• Praktische Erfahrung mit AI und Machine Learning ist erforderlich.
• Ausgezeichnete Programmierkenntnisse, vorzugsweise in Python.

Aufgaben

• Entwicklung von Anwendungen mit AI, Machine Learning und Computer Vision.
• Zusammenarbeit in internationalen Projekten in verschiedenen Disziplinen.

Kenntnisse

AI und Machine Learning

Programmierung (Python)

Interdisziplinäre Zusammenarbeit

Ausbildung

Studium in Informatik oder verwandten Bereichen

Jobbeschreibung

The particular strength of the Fraunhofer Institute for Electronic Nano Systems ENAS lies in the development of smart systems - so-called intelligent systems for various applications. The systems combine electronic components, micro and nano sensors and actuators with interfaces for communication. Fraunhofer ENAS develops individual components, the technologies for their production as well as system concepts and system integration technologies and transfers them into practical use. Fraunhofer ENAS accompanies customer projects from the idea to the design, technology development or implementation using existing technologies, right through to the tested prototype.

The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is on semiconductor manufacturing and medical technology.

Are you passionate about cutting-edge research at the intersection of healthcare, technology and data science? Join our team in European projects and work in an international team of experts from different disciplines such as proton therapy, computer science, applied mathematics, detector physics and medical physics.

We are currently looking for students for Master's theses, internships and student assistants. We can discuss our ideas together to find the right job for you.

What you bring to the table

• You already have some practical experience with AI and machine learning algorithms? Then you've come to the right place.
• Excellent programming skills (preferably in Python) are required.
• A strong interest in interdisciplinary work at the intersection of medical engineering, physics, mathematics and data science is essential.
• Still studying in Chemnitz, Mittweida or the surrounding area.
• A grade point average of < 2 is preferred.

We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability.

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.

Interested? Apply online now. We look forward to getting to know you!

Dr. Jan Langer will be happy to answer any questions you may have about the position. Please submit your questions here via our recruiting portal.

Fraunhofer Institute for Electronic Nano Systems ENAS

www.enas.fraunhofer.de

Requisition Number: 73204
Application Deadline: 12/31/2024