Description
My client are looking for a team of Data Scientists.
Our customer is testing a new system for detecting defects at the end of the packaging line. There already exists a training set with tagged images used for a prototype deep learning algorithm. The assignment is to continue this project in a parallel track to benchmark detection accuracy using other methodologies (RNN, auto encoders, cluster learning, Predictive Networks etc.) and toolkits (Tensor flow, Caffe2). The aim is by combining supervised and unsupervised methods we will be able to correctly detect and classify defects more efficiently than using fully supervised methods as well as an uplift in classification accuracy by benchmarking a broader spectrum of deep learning algorithms. Our customer is looking for a team of Data Scientist with experience in Image recognition and using cloud services for leveraging deep learning tool kits and setting up an efficient and scalable environment.
Required skills:
- Machine learning and Statistical Modelling
- Image Recognition and Deep Neural Networks
- Python
Preferred skills:
- MS Azure and container services
Personal/Education Preferred:
- Mathematics/Statistics/Data Science/Computer Science
Start:
Duration: 3 month with potential extension
Project Location: LUND
Working language: English