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Graphen

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About

Graphen is building next-generation AI platforms based on graphs to produce full brain functions and generate novel industry solutions. They offer innovative solutions across industries, including AI-powered digital humans, AI drug design, in-car AI assistants, fraud detection, and cybersecurity. Their AI technologies are applied across various domains such as cognitive security, employee productivity, intelligent machines, big data management, and reasoning.

Platform
Web
Task
ai platform

Features

in-car ai assistants

ai-powered digital human

ai tools for medical research and drug design

ai finance knowledge platform

self-defense ai cybersecurity

real-time transaction fraud detection

personalized medical design

precision drug optimization

Job Opportunities

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Graphen

Research Scientist

Graphen builds next-generation AI platforms based on graphs for industry solutions, including digital humans, drug design, and cybersecurity. They aim to advance AI for the well-being of mankind.

scienceonsiteNew York, USfull-time

Education Requirements:

  • Ph.D. or Master's Degree in Computer Science, Electrical Engineering, Statistics, Mathematics, Physics, Computational Finance, Industrial Engineering, Financial Engineering, Operations Research or a similar quantitative field. Ph.D. preferred.

Experience Requirements:

  • Expertise in Machine Learning, Data Mining, Pattern Recognition, Natural Language Processing or Computer Vision.

  • Publications in peer-reviewed journals and conferences.

  • Experience or interest in programming in one or more of these languages: C++, C, Java, Python, Go, etc.

Responsibilities:

  • Lead in cutting-edge AI research and develop innovative approaches in the financial/healthcare domains to solve real-world problems. Publish your results and grow Graphen’s IP portfolio.

  • Contribute ideas, develop prototypes and implement efficient and effective algorithms for Graphen solutions.

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Software Engineer

Graphen builds next-generation AI platforms based on graphs for industry solutions, including digital humans, drug design, and cybersecurity. They aim to advance AI for the well-being of mankind.

Education Requirements:

  • BS or MS degree in Computer Science, Computer Engineering or similar technical field of study preferred.

Experience Requirements:

  • 3-5 years of working experience in system software development.

  • Software development experience in one or more general purpose programming languages including but not limited to: Java, C/C++, C#, Objective C, Python, JavaScript or Go.

  • Good knowledge of Data Structures and Algorithms. Parallel and Distributed Programming skills are a bonus.

Responsibilities:

  • Design, implement, test, integrate, deploy, maintain and improve various components of Graphen AI platform and solutions.

  • Conduct extraction, cleansing, exploration, transformation and loading of data from various sources to Graphen data store for different applications.

  • Perform customization of Graphen solutions to suit specific customer needs.

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Data Scientist Intern

Graphen builds next-generation AI platforms based on graphs for industry solutions, including digital humans, drug design, and cybersecurity. They aim to advance AI for the well-being of mankind.

Education Requirements:

  • Currently studying or graduated from a scientific or quantitative field (Preferably MS or PhD)

Experience Requirements:

  • Proficiency processing large datasets with statistical packages

  • Software development experience as demonstrated through course work, research projects or open source activities, preferably in Python or C++

  • Applied Experience with Machine Learning and Big Data technologies

  • Previous experience or course work in finance, business, economics, and/or biostatistics is a plus

Responsibilities:

  • Develop AI trading strategies in various financial market (Forex, stock, ETF, etc.) for finance domain

  • Develop AI analyses in genome and/or proteome data in the medical domain

  • Work with large data sets and solve difficult, non-routine analysis problems

  • Translate unstructured, complex business problems into Machine Learning framework

  • Prototype, refine, deploy and monitor predictive models and decisions agents that are used in automation and analysis tasks

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