Student Assistant Applied Machine Learning
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Opportunities to write a master's or bachelor‘s thesis. Develop and test new deep learning architectures. Analyze and preprocess different data types, mostly…...
The Fraunhofer-Gesellschaft (www.fraunhofer.com) currently operates 76 institutes and research institutions throughout Germany and is the world’s leading applied research organization. Around 30 800 employees work with an annual research budget of 3.0 billion euros.
Future. Discover. Together.
The Group for Applied Machine Learning at the Department for Artificial Intelligence at Fraunhofer Heinrich Hertz Institute in Berlin is looking for a student assistant to strengthen its scientific activities and to develop innovative solutions, especially in the context of interdisciplinary collaborations. Become a part of our team and join us on our journey of research and innovation!
What you will do
Develop and test new deep learning architectures
Analyze and preprocess different data types, mostly climate-, weather- and geo-data
Conduct and document Deep Learning experiments
Experience applied science in exciting projects
Prepare material for publications
Review relevant literature and data
What you bring to the table
Study of mathematics, computer science, physics or similar with good to very good grades
Strong programming skills in Python with knowledge of frameworks such as NumPy, Pytorch, Pandas etc
Experience in using Linux (Ubuntu) via the terminal
Writing clean and concise code
Diligence in implementing, testing and documenting algorithms
Curiosity about a deeper understanding of Deep Learning architectures
Interest in the intersections of AI and Climate science and AI and Epidemiology
What you can expect
Fascinating challenges in a scientific and entrepreneurial setting
Attractive salary
Modern and well equipped workspace in central location
The position is initially limited to 6 months. An extension is explicitly desired.
Great and cooperative working atmosphere in an international team
Opportunities to write a masters or bachelor‘s thesis
Flexible working hours
Opportunities to work from home
The position is initially limited to 1 year. An extension is explicitly desired.
The monthly working time is 80 hours. This position is also available on a part-time basis. 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!
Contact:
Dr. rer. nat. Jackie Ma
Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute HHI
Requisition Number: 73611 Application Deadline: 06/30/2024
Information :
- Company : Telecommunications, Heinrich Hertz Institute
- Position : Student Assistant Applied Machine Learning
- Location : Berlin
- Country : DE
How to Submit an Application:
After reading and knowing the criteria and minimum requirements for qualifications that have been explained from the Student Assistant Applied Machine Learning job info - Telecommunications, Heinrich Hertz Institute Berlin above, thus jobseekers who feel they have not met the requirements including education, age, etc. and really feel interested in the latest job vacancies Student Assistant Applied Machine Learning job info - Telecommunications, Heinrich Hertz Institute Berlin in 31-05-2024 above, should as soon as possible complete and compile a job application file such as a job application letter, CV or curriculum vitae, FC diploma and transcripts and other supplements as described above, in order to register and take part in the admission selection for new employees in the company referred to, sent via the Next Page link below.
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Post Date : 31-05-2024
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