PhD/Masters/Bachelors degree in Computer Science, Computer Engineering, Machine Learning, Statistics or a related field with relevant work experience. Data engineering (especially working with unstructured data) Data ingestion/indexing techniques.

5+ years of experience across a breadth of data science, AI and machine learning disciplines including, but not limited to: forecasting, natural language processing (topic modeling, semantic search, text classification), deep learning and GPU-based algorithms (CNN, LSTM), computer vision.

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.

Expertise in several areas of computer science such as introduction to programming, data structures and algorithms, basic cyber-security, architecture, and system programming. The Department of Computer Science & Engineering at the University of Connecticut invites applications for a non-tenure track position at the rank of Lecturer at the Storrs campus.

Aerospace Engineering, Automotive Engineering, Biomedical Engineering, Chemical Engineering, Computer Engineering, Engineering, Engineering Mechanics, Engineering Physics, Industrial and Operations Engineering, Industrial Engineering, Materials Science and Engineering, Mechanical Engineering, Production Engineering, Project Engineering & Management, Biomedical Science, Computer and Information Science, Data Processing/Analytics/Science.

A Masters’ degree in computer science, AI/ML, data science, mathematics, statistics, applied linguistics/psychology/neuroscience and related fields, or 2+ years of equivalent experience.

Bachelor of Science degree from an accredited course of study in engineering, engineering technology (includes manufacturing engineering technology), chemistry, physics, mathematics, data science, or computer science.

Experience leveraging Esri's software capabilities including, mapping, field operations, spatial analysis and data science, 3D visualization and analytics, data management, and developer APIs.

A Master's or PhD degree in biostatistics, data science, biomedical informatics, epidemiology, public health, computer science, applied mathematics, engineering, or a related field.

Qualifications• Bachelor’s degree in Computer Science required• Master’s degree in Computer Science required• 3 years of experience managing, motivating, and developing data science teams for high performance• 5 years of experience with data science and analytics technologies such as Python, SQL, Tableau, Alteryx, AWS Redshift and Lambda, and/or Google Cloud Platform.

We are hiring a Senior Statistical Analyst to leverage cutting-edge data science tools and methodologies on real-world clinical data for scientific research in precision medicine.

Join us to expand your technical career through the lens of work on many novel projects and use cases to expand your proficiency in real-world health care data, statistical analysis, data science and AI skills on healthcare.

Data science, machine learning, optimization models, Master's degree 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, Using open source frameworks (for example, scikit learn, tensorflow, torch.

The successful candidate has a scientific background in operations research, engineering or other STEM field and has expertise in one or more of the following areas: data science, data analytics, data engineering, data visualization, supply chain planning, statistics, machine learning, predictive modeling, decision analysis under uncertainty, artificial intelligence, Python and/or R, app development, and Tableau dashboard development.

PhD in data science, computer science, management information systems, mechanical engineering, electrical engineering, power systems engineering, or related field. Master’s degree in electrical engineering, mechanical engineering, power systems engineering, data science, statistics, computer science, management information systems, or related field.