MASTER THESIS Development of a human-in-the-loop method for text document classification

Berufsbezeichnung:

MASTER THESIS Development of a human-in-the-loop method for text document classification

Unternehmen

Andritz

Stellenbeschreibung

MASTER THESIS Development of a human-in-the-loop method for text document classification – ID 15065en_USGrazEvery day, ANDRITZ continues to deliver successful innovative solutions to our customers globally. Why are we so successful? Because we are passionate and love what we do! We are at the forefront of future engineering technologies, with solutions that ensure the success of our clients in key industries that are shaping the future of the world we live in.As part of your master’s thesis at ANDRITZ, you will gain comprehensive insight into an internationally operating company and have the opportunity to make your first professional contacts for your future career.We are looking for a student for a masterthesis, who will be employeed on a 6h/week basis for 6 months.TOPIC OF THE THESIS

• State of the art analysis.
• In-depth analysis of dataset.
• Definition of cleaning/filtering requirements.
• Definition of requirements on the human-in-the-loop procedure.
• Design and method development in MS Azure.
• Testing.
• Documentation.

YOUR PROFILE

• Profound knowledge in Python.
• Master student in the field of data science, computer science, or similar.
• Thesis can be written either in German or in English

OUR OFFER
Andritz AG offers a secure job in an innovative and international company with long-term development opportunities.

• Talent & leadership programs
• Flexible working time model
• Various employee discounts
• Subsidized company restaurant
• Parking spaces & public accessibility
• Bike Leasing

In Austria we are legally obliged to announce at least a gross monthly salary of EUR 3.207,73 for this position (fulltime).Bitte bewerben Sie sich über unsere Website:andritz.com/careersENGINEERED SUCCESS

Erwartetes Gehalt

€3207.73 per month

Standort

Graz, Steiermark

Jobdatum

Tue, 29 Oct 2024 23:38:10 GMT

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