Research Scientist Intern
Newark, DE 
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Posted 7 days ago
Job/Internship Description

The Innovation and Development Division (IDD) drives the innovation strategy for the Hubs and Operations, and contributes to the Group's transformation. It is responsible for imagining, developing and incubating new solutions until they are brought to market, particularly when it comes to offers with a high technological content (including digital and IT). IDD gathers more than 3,000 employees from 70 nationalities at 60 sites.

How will you CONTRIBUTE and GROW?

Your mission, in short
Refactor existing code bases, improve code efficiency and maintainability.
Building infrastructure for execution of Molecular dynamics (MD) simulations in refactored computational pipeline.
Building and refining machine learning and deep learning solutions to accelerate material design and model development.
Working with a global team across US, Canada and Paris.

Job Description

  • Run exploratory tests to identify valuable and innovative insights from data.

  • Research and implement cutting-edge techniques in data science to solve real business problems.

  • Contribute to the various phases of data science product development (business needs identification, design, data understanding, data mining, data visualization, data modeling, testing, tuning, deployment and monitoring) and potentially deliver your own PoCs ('Proof of Concept').

  • Gain business and data understanding from conversations with different stakeholders.

  • Work both independently and collaboratively with Air Liquide research scientists, engineers, and clients from business to accomplish complex tasks that deliver demonstrable value to the Group

__________________Are you a MATCH?

Required

  • You are a master's, or doctoral student in computer science, chemical engineering, mathematics, statistics, or a related field.

  • Familiar with Molecular dynamics (MD) simulations and the Linux operating system.

  • You have good knowledge of Python, and the tools and libraries in the data science ecosystem (pandas, Numpy, scikit-learn).

  • You have an interest in answering challenging, open-ended research questions with real-world impact.

  • You have good knowledge of statistics and how statistical methods applied to data can tell the story.

  • You are recognized by your analytical and problem-solving skills, clean and well written code with high time efficiency, as well as clear visualization that tells stories.

  • You are eager to learn everyday.

Preferred

  • You are familiar with git and code repositories such as GitHub and GitLab.

  • You have experience with deep learning frameworks (Pytorch, TensorFlow).

  • You have a good understanding of Deep Learning, and are willing to learn applicable deep learning structures for business use cases.

  • You have previous experience working with large datasets.

The candidate must have valid unrestricted employment authorization in the U.S. and must not require visa sponsorship now or in the future.

Our Differences make our Performance


At Air Liquide, we are committed to build a diverse and inclusive workplace that embraces the diversity of our employees, our customers, patients, community stakeholders and cultures across the world.


We welcome and consider applications from all qualified applicants, regardless of their background. We strongly believe a diverse organization opens up opportunities for people to express their talent, both individually and collectively and it helps foster our ability to innovate by living our fundamentals, acting for our success and creating an engaging environment in a changing world.


We are an equal opportunity employer. Everyone will be considered for employment, promotions, transfers, and other conditions of employment without regard to race, color, religion, sex, national origin, physical or mental handicap, age, Vietnam era veteran status, disabled veteran status, marital status, sexual orientation, political affiliation, or any other basis prohibited by state or federal law.

 

Position Summary
Start Date
As soon as possible
Employment Type
Full Time
Period of Employment
Open
Type of Compensation
Paid
College Credits Earned
No
Tuition Assistance
No
Required Student Status
Open
Preferred Majors
Other
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