We are looking for outstanding undergraduate and graduate students for summer internships in applied machine learning. Natural language processing (NLP) is generally concerned with automatically processing documents into a machine readable representations, and state-of-the-art NLP is increasingly tackled using deep neural networks trained on large amounts of data. However, a number of challenges emerge when labeled data is limited. The theme of this year’s SCALE is automatically extracting structured information (e.g. people, organizations, locations, etc.) from unstructured text and dealing with the challenges that emerge when labeled training data is not readily available.
The workshop is a good opportunity for undergraduates to obtain research experience and for graduate students to pursue challenging technical problems in a collaborative environment. Previous workshops have resulted in fruitful collaborations beyond the workshop itself and academic publications at top international conferences.
Some example technical problems in the scope of the workshop:
Experience with machine learning software packages, e.g. TensorFlow or PyTorch, is a plus but not required.
You can find information on our past workshops at: https://hltcoe.jhu.edu/research/scale/
The HLTCOE is an independent research center within Johns Hopkins University and located a short walk (or shuttle ride) away from the Homewood Campus. We work closely with the Center for Language and Speech Processing (CLSP), the Department of Computer Science, Electrical and Computer Engineering, and Applied Math and Statistics.
The HLTCOE GRID computing cluster consists of over 1500 CPU cores, 15 TB of RAM and 700 TB of storage. Additionally, we have over 170 GPUs for machine learning research including a NVIDIA DGX-1. All nodes are interconnected by 40 Gbe network.
These are (well) paid internships! Housing and transportation costs are also covered, in addition to catered meals.
Applicants must be US citizens.