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Selvita

Summer Internship in Computational Chemistry / Machine Learning

Internship - Civil law contract
Post offered
Summer Internship in Computational Chemistry / Machine Learning
Form
Civil law contract
Recruitment date
11.04.2024 – 31.05.2024
Location
Kraków
Number of vacancies
2
Official e-mail address
careers@selvita.com
Requirements
  • Student status (preferably during the 4th year).
  • Field of study focused on chemistry, computational chemistry, cheminformatics, machine learning, or a related discipline.
  • Availability for a 3-month internship (1st of July to 30th of September 2024), with a minimum availability of 35-40 hours per week.
Responsibilities
  • Daily collaboration with an experienced research team.
  • Active participation in research projects.
Employment conditions / Company offers
  • Chance to gain practical experience under the guidance of experienced mentors.
  • Daily cooperation and know-how exchange with an experienced research team.
  • Paid internship with a regulated legal form (internship agreement).
  • Opportunity to gain practical experience in the Computational Chemistry or Machine Learning Team.
How to apply
Use this link to apply - https://recruitment.elevato.net/en/summer-internship-in-computational-chemistry-machine-learning,j,418
Sector trade
Science
Additional information
The Selvita internship program is designed for students seeking their first valuable professional experience. Many interns return to Selvita after graduation to continue their professional development. This year, the program focuses on the Computational Chemistry Department. What does the recruitment timeline look like in 2024? We accept applications until May 31st. Selected candidates will be invited to an online recruitment meeting with representatives from the Computational Chemistry Department. By June 10th, all applicants will receive decisions along with internship offers for those with the best results. The internship begins on July 1st. Good luck!

Office of Careers Service is not responsible for the content and credibility of published offers.

Published by: Piotr Rapciak

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