Scientific Programmer for Explainable AI Applications (0,8 FTE) at Universiteit Leiden
Leiden, Zuid-Holland, Netherlands -
Full Time


Start Date

Immediate

Expiry Date

12 Jun, 25

Salary

3.378

Posted On

09 May, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Education Management

Description

Vacaturenr.
15459
Functie-categorie
Niet-wetenschappelijke functies
Omvang (fte)
0,8
Extern/intern
Extern
Locatie
Leiden
Geplaatst op
11 februari 2025
Sluitingsdatum
17 maart 2025
The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are looking for a:

SCIENTIFIC PROGRAMMER FOR EXPLAINABLE AI APPLICATIONS (0,8 FTE)

Join our exciting research project on Explainable AI for Predictive Maintenance as Scientific Programmer and work together with our research team and industrial partner to solve challenging real-world optimization problems.
As part of the Natural Computing group of LIACS, you will work together with highly skilled professors and PhD candidates in the fields of evolutionary and Bayesian single- and multi-objective optimization, machine learning and explainable artificial intelligence, you will help to make their code re-usable, available and easy to maintain and you will co-develop several software libraries to be released open-source.
We are seeking a candidate with strong skills in Python programming, Git and DevOps with interests in academic projects including artificial intelligence and optimization algorithms.

Responsibilities
  • Develop and maintain high-quality, reusable, and well-documented software for AI-driven predictive maintenance;
  • Collaborate with researchers to translate prototypes into robust, scalable, and maintainable code;
  • Ensure reproducibility and accessibility of research software through best practices in software engineering, version control (Git), and DevOps;
  • Develop and manage open-source software libraries for AI and optimization research;
  • Support PhD candidates and researchers in improving code quality, testing, and deployment strategies;
  • Engage in discussions with industrial partners to align software development with real-world applications;
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