Globus Labs Intern

Department ​
 
RINL Globus Labs - Materials

About the Department

​

Globus (www.globus.org) is a sustainable, non-profit business within the University of Chicago delivering solutions to the research community worldwide. Globus develops and provides critical services that support scientific research for governmental, academic, and commercial organizations in a wide range of disciplines including life sciences, physics, and astronomy. We develop, operate, and sell commercial-quality, cloud-based software application and platform services used by tens of thousands of researchers to manage their large– and growing– data management challenges. We have offices located at 401 North Michigan Avenue in the heart of downtown Chicago and remote employees who work from home.

Job Information ​
 

Job Summary:

As an intern with the Globus Labs team, the focus of this position will be to assist in the development and deployment of new software services to help researchers publish and share their data and to solve problems in domains ranging from materials science, chemistry, catalysis, x-ray science, and more. We’re looking for highly skilled students and young people skilled in the techniques of data preprocessing, machine learning, and also building and supporting Python services and systems. The position will be remote, primarily appointed at the University of Chicago with collaborations at Argonne National Laboratory.

Responsibilities:

• Assist in the development and deployment of new software.
• Assist researchers publish and share data.
• Process data through Python services and systems.

Additional Requirements ​​
 

Education, Experience or Certifications:

Education:

• Currently enrolled in an undergraduate degree program.

Experience:

• One year of relevant programming experience developing, implementing, debugging, and maintaining applications or data services written in Python.
• Experience with a distributed version control system (e.g., Git).
• Python programming.
• Machine learning frameworks such as Tensorflow, Keras, or Pytorch.
• Developing user-facing software.
• One year of experience developing machine learning models and data processing pipelines.
• Experience with the latest and greatest web standards, including HTML5 and CSS3.

Working Conditions and Physical Requirements:

• This position is a remote position.

Required Documents:

• Resume/CV

When applying, the document(s) MUST  be uploaded via the My Experience page, in the section titled Application Documents of the application.

Benefit Eligibility ​
 
No

Requires Compliance with University Covid-19 Vaccination Requirement
 

Yes

Pay Frequency ​
 
Hourly

Pay Range
 
Depends on Qualifications

Scheduled Weekly Hours ​
 
37.5

Union ​
 
Non-Union

Job is Exempt
 
No

Drug Test Required
 
No

Motor Vehicle Record Inquiry Required
 
No

Health Screen Required
No

Posting Date ​
 
2022-06-22-07:00

Remove from Posting On or Before ​
 
2022-12-22-08:00

Posting Statement: ​​
 

Employees must comply with the University’s COVID-19 vaccination requirements. More information about the requirements can be found on the University of Chicago Vaccination GoForward .
The University of Chicago is an Affirmative Action/ Equal Opportunity /Disabled/Veterans Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national or ethnic origin, age, status as an individual with a disability, protected veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.

 

Staff Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.

 

We seek a diverse pool of applicants who wish to join an academic community that places the highest value on rigorous inquiry and encourages a diversity of perspectives, experiences, groups of individuals, and ideas to inform and stimulate intellectual challenge, engagement, and exchange.

 

All offers of employment are contingent upon a background check that includes a review of conviction history.  A conviction does not automatically preclude University employment.  Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.

 

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