Merck & Co., Inc. Kenilworth, N.J., U.S.A. known as Merck in the United States and Canada, is a global health care leader with a diversified portfolio of prescription medicines, vaccines and animal health products. Today, we are building a new kind of healthcare company – one that is ready to help create a healthier future for all of us.
The intern in the Image Data Analytics Team of Scientific Informatics Department will develop techniques for quantitative analysis of 2D, 3D multi-dimensional images towards development of biomarkers in biological datasets to support drug development. The researcher will apply machine learning, deep learning, data mining, image processing and signal processing techniques to extract meaningful information from high-dimensional, multi-modality datasets. This intern research will be an opportunity to apply cutting edge data analysis techniques to the emerging field with exciting and impactful applications in drug discovery and development.
• Must be currently pursuing MS or PhD candidate in one of the following areas: Electrical Engineering, Computer Science, Biomedical Engineering, Bioinformatics, Applied Mathematics, Statistics
• Should be able to work full time for 10-12 weeks in summer of 2019 and return to school in fall of 2019 on completion of the assignment.
Required Experience and Skills:
• Knowledge in mathematical algorithms in areas such as machine learning, deep learning, pattern recognition, data mining, image processing, computer vision, signal processing, bioinformatics, statistics
• Research experience in biomedical image processing (such as histology-based, CT, MR etc.) to medical, healthcare and/or pharmaceutical applications
• Research experience in analyzing multimodal datasets
• Ability to plan and schedule daily computing, research and reporting activities to meet established timetables and objectives
• Excellent verbal and written communication skills are required.
Preferred Experience and Skills:
• Experience in software packages e.g. Python, Matlab, R, C++, Java
• Experience in deep learning packages such as TensorFlow, Caffe, Keras, PyTorch, MXNet
• Experience in high performance computing, GPU computing, and Cloud computing
• Experience in bioinformatics and genomics
• Experience with big data tools e.g. Hadoop, Spark