PhD Candidate: AI Tax Research & NLP Innovations

Unist

Wrocław

Hybrid

PLN 54,000 - 56,000

Full time

14 days+

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Benefits offered by this job

PhD Scholarship (5000 PLN/month for 11
Mentorship by AI and tax-law experts
Flexible study-friendly environment

Job summary

Wroclaw University of Science and Technology invites applications for a PhD position under the FIRST TEAM FENG program. You will research AI techniques for automatic tax data analysis, focusing on semantic search, summarisation of tax rulings, and repository development.

Engage with experts in NLP, LLMs, and tax law, publish results in top journals, and enjoy a scholarship of 5000 PLN monthly for 11 months. Flexible, research-driven environment in Poland.

Qualifications

  • Master's degree or equivalent in Computer Science, Mathematics, Data Engineering, Law, or related fields.
  • Enrollment in a doctoral school.
  • Proficiency in English (B2) for reading technical literature and writing scientific papers; Proficiency in Polish (C1) for domain data understanding including Polish tax interpretations.

Responsibilities

  • Develop AI algorithms to support semantic search and generate summaries of tax rulings.
  • Collaborate on building a semantic repository for tax rulings and court decisions.
  • Prepare scientific publications based on research outcomes.

Skills

Python
NLP
Machine learning
Co-pilot

Education

Master's degree or equivalent in Computer Science, Mathematics, Data Engineering, Law, or related fields

Tools

PyTorch
Scikit-learn
Hugging Face Transformers
Cursor

Job description

Wroclaw University of Science and Technology invites applications for a PhD position under the FIRST TEAM FENG program. You will research AI techniques for automatic tax data analysis, focusing on semantic search, summarisation of tax rulings, and repository development.

Engage with experts in NLP, LLMs, and tax law, publish results in top journals, and enjoy a scholarship of 5000 PLN monthly for 11 months. Flexible, research-driven environment in Poland.

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