Dein persönlicher KI-Karriere-Agent
University Assistant Prae-Doc(m/w/x)
NLP research for social sciences in an international lab. Prior research experience preferred. 14 salaries per year, ample computing resources.
Anforderungen
- Bachelor's or master's degree in computer science, informatics, data science, HCI, computational social science, machine learning, statistics, or computational linguistics
- Knowledge of NLP, large language models, machine learning, experimental design, and statistical analysis
- Interest in social science discipline and methodologies
- Prior research experience (thesis or lab work)
- Publications in top ML or NLP conferences (not required)
- Very good English communication and writing skills
- German language knowledge (B2) or willingness to learn
- Python knowledge preferred
- Agentic coding experience is a plus
- Initiative-taking
- Striving for independence and autonomy
- Desire to do research in the field
- Participation in academic community
- Curiosity about the world
- Self-motivation
Aufgaben
- Conduct research for publication in premier conferences and journals
- Run lab sessions and assist with lectures, examinations, and thesis supervision
- Mentor and collaborate with students at all levels
- Contribute to funding proposals
- Participate in scientific events like conferences and workshops
- Write a dissertation
- Assist with organizational and administrative tasks
Ausbildung
- Bachelor-Abschluss
Sprachen
- Englisch – verhandlungssicher
- Deutsch – fortgeschritten
Tools & Technologien
- Natural Language Processing
- Large Language Models
- Machine Learning
- Statistical Analysis
- Python
- Agentic coding
Benefits
Attraktive Vergütung
- 14 salaries per year
Moderne Technikausstattung
- Ample access to computing resources
Weiterbildungsangebote
- Internal and external training opportunities
Sonstige Vorteile
- Generous social services
- Visa assistance
Gefällt dir diese Stelle?
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University Assistant Prae-Doc(m/w/x)
NLP research for social sciences in an international lab. Prior research experience preferred. 14 salaries per year, ample computing resources.
Anforderungen
- Bachelor's or master's degree in computer science, informatics, data science, HCI, computational social science, machine learning, statistics, or computational linguistics
- Knowledge of NLP, large language models, machine learning, experimental design, and statistical analysis
- Interest in social science discipline and methodologies
- Prior research experience (thesis or lab work)
- Publications in top ML or NLP conferences (not required)
- Very good English communication and writing skills
- German language knowledge (B2) or willingness to learn
- Python knowledge preferred
- Agentic coding experience is a plus
- Initiative-taking
- Striving for independence and autonomy
- Desire to do research in the field
- Participation in academic community
- Curiosity about the world
- Self-motivation
Aufgaben
- Conduct research for publication in premier conferences and journals
- Run lab sessions and assist with lectures, examinations, and thesis supervision
- Mentor and collaborate with students at all levels
- Contribute to funding proposals
- Participate in scientific events like conferences and workshops
- Write a dissertation
- Assist with organizational and administrative tasks
Ausbildung
- Bachelor-Abschluss
Sprachen
- Englisch – verhandlungssicher
- Deutsch – fortgeschritten
Tools & Technologien
- Natural Language Processing
- Large Language Models
- Machine Learning
- Statistical Analysis
- Python
- Agentic coding
Benefits
Attraktive Vergütung
- 14 salaries per year
Moderne Technikausstattung
- Ample access to computing resources
Weiterbildungsangebote
- Internal and external training opportunities
Sonstige Vorteile
- Generous social services
- Visa assistance
Gefällt dir diese Stelle?
BetaDein Career Agent findet täglich ähnliche Jobs für dich.
Über das Unternehmen
TU Wien
Branche
IT
Beschreibung
Das Institut für Materialchemie entwickelt und untersucht heterogene Katalysatoren, insbesondere innovative Materialien durch Kombination von Sulfiden und Oxiden, mit Fokus auf die Nutzung von CO2 aus Abgasströmen.
Noch nicht perfekt?
- University of Vienna
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Vollzeitnur vor OrtKeine AngabeWienab 60.000 / Jahr