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Doctorate Degree in Medicine, Biomedical Informatics, Epidemiology, Computer Science, Data Science, Public Health, Economics, Biostatistics, Health Policy, Statistics, or Biometrics or equivalent experience.
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Education Preferred: Master's Degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field.
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Our researchers have a broad range of expertise related to computer science and electrical engineering, such as AI/ML, algorithms, digital signal processing, audio engineering, image processing, computer vision, data science & analytics, distributed systems, cloud, edge & mobile computing, computer networking, and IoT.
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Preferred: Master's or PhD in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field.
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Responsible for developing and delivering courses and programs in Computer Science in one or more of the following areas: Software Development, Artificial Intelligence, Cloud Computing, Data Science, Cybersecurity and Enterprise (mainframe) Computing.
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Bachelor’s degree (or foreign education equivalent) in Applied Mathematics, Computer Science, Engineering, Information Technology, Information Systems, Information Management, Mathematics, or a closely related field and five (5) years of experience as a Director, Data Science (or closely related occupation) launching, operating, leading and implementing document processing, computer vision, and Deep Learning (DL) practices using TensorFlow, Keras, MXNET, or H2O.
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MS in Computer Science and 6 years as a Salesforce architect, OR. BS in Computer Science and 8 years as a Salesforce architect. Lead the Salesforce Development Team in the design and development of Salesforce custom solutions comprising of work in Apex, Visual Force, Salesforce APIs, Lightning, and data migration.
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A combined 5-year BS-MS program, a minor in computer science, a Certificate in Data-Intensive Computing, and several joint programs (BS in Computer Science/ MBA , BS in Computational Physics, BA in Social Sciences Interdisciplinary – Cognitive Science Concentration, BS in Bioinformatics and Computational Biology – CSE concentration) as well as MS and PhD programs in Computer Science & Engineering.
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MS/PhD in a quantitative or scientific discipline (e.g. engineering, mathematics, statistics, computer science) with 8-10+ (BS) 6-8+ (MS) or 3-5+ (PhD) years of relevant data science/analytics experience in the pharmaceutical industry.
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PhD degree in computer science, computational biology, bioinformatics, quantitative science or related field. Participates in creating data algorithms and specialized computer software to identify and classify components of a biological system (i.e. DNA and protein sequences.
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Master’s Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science) Bachelor’s Degree in related field (e.g. Data Science, Predictive Analytics, Statistics, Marketing Analytics, Applied Mathematics, IT.
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Expertise in open source data science technologies such as Python, R, Spark, SQL. 5+ years of experience using AI/ML , data science software (e.g., Python-based tools) The Senior AI Engineer will have a strong technical background and demonstrated experiences in Gen AI, Data Science and AI/ML. The ideal candidate will be responsible for delivery of analytical models and AI solutions.
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Contribute towards advancing the AI Engineering and Data Science discipline in Ford Pro through the Community of Practice, including but not limited to driving data best practices, improving analytical processes, scaling knowledge and tools, and mentoring other data scientists.
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Algorithm Development, Artificial Intelligence, Embedded Systems, Electronic Warfare, Image Processing, Machine Learning, Military Vehicles, Modeling/Simulation, Robotics/Automated Systems, Sensors Integration, System Engineering, Testing, Aerospace, Sensors/Optics, Autonomous Systems, Data Analytics/Science, ISR & Tactical Systems, Threat Systems.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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