Project to develop a Smart Baby Suit
As part of a unique collaboration between the Artificial Intelligence and Biophysics departments, the Baby & Child Research Center and two industrial companies, a Smart Baby Suit is being developed that can measure the behavior and psychophysiological characteristics of babies. In the long term, such measurements will help to detect abnormal development early on.
For this project we are looking for 2 student assistants with an interest in time-series modeling, transfer learning and making Deep Learning models applicable. The student assistants will work together in a multidisciplinary team of academics at the university and in industry. For the project, the student assistants will apply an existing model trained on a similar dataset to new Smart Baby Suit recordings from the Baby & Child Research Center, build software that allows fine-tuningby researchers, and present results to the team. The uniqueness of this job is that it offers the opportunity to gain experience in applying AI models in a real-world setting and to contribute to the development of innovative research methods and instruments.
Do you recognize yourself in this profile?
- Master student at Radboud University, Artificial Intelligence / Computer Science
- Reliable, organized, precise
- Good understanding of Machine Learning algorithms & principles
- Good programming skills (Python)
- Experience with Machine Learning toolboxes (preferably PyTorch)
- Intrinsically interested in research and a real team player
Appointment will be arranged via Campus Detachering (see https://www.ru.nl/studenten jobs/). Ideally, each student assistant spends12 hours per week on this project. The distribution of the hours over the week is flexible. 650 hours are available in total. Entrance is per 15 Nov 2020, until June 2021.You can send your application (short cover letter and your CV) to Drs. Elsbeth van Dam (firstname.lastname@example.org). Interviews start as soon as the first applications are in. The vacancy will be closed no later than November 15, 2020.