Machine Learning/Statistics Internship at Siemens Healthcare As one of the leading providers worldwide, Siemens Healthcare helps to optimize processes in healthcare and to better care for patients. The Computer-Aided Diagnosis R&D Group within Image and Knowledge Management at Siemens has a proven record of delivering trend-setting computer vision, pattern recognition and machine learning software applications for clinicians and other medical professionals. Internship positions are available for motivated Ph.D. students working in machine learning/data mining, statistics, or biostatistics. As an intern, you will join the CKS team of scientists in solving exciting and challenging research problems in the medical domain. Our research is motivated by decision-support and data processing problems arising in the medical domain and related health areas; experience or interest in these areas is a plus. All interns are strongly encouraged to publish their work. Siemens HealthCare is located in Malvern, PA. Malvern lies within the Main Line area of the Philadelphia suburbs (with downtown Philly less than an hour's drive away). --Intern/Co-Op Requirements : Academic Degree: PhD Track, with Masters Coursework Completed Major: Computer Science, Electrical Engineering, Statistics/Biostatistics Minimum GPA: 3.0 Technical skills: Hands on experience with various machine learning techniques, C++/Matlab/R proficiency, fast prototyping skills, precise scientific writing skills to document techniques and results, familiarity with statistical methods for diagnostic medicine is a plus Internship duration: Summer (At least 12 weeks) Preferred hours/week: 40 hours/week Compensation: This internship offers a competitive hourly wage. --Application Instructions : To apply, please visit our career web-site at www.usa.siemens.com/careers Click on "US Jobs." Go to the "Search by Requisition ID" field and type in requisition #85908 and follow the application instructions. Please submit your application by April 15th, 2010 to be considered for this opportunity. Thank you!
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