Search

Student Research Assistant (m/f/d)

PIK
locationPotsdam, Deutschland
VeröffentlichtVeröffentlicht: vor 4 Tagen
Wissenschaft

Tätigkeitsprofil:

Key responsibilities:

  • Develop new features for our annotation platform and other tools
  • support researchers that use our platform (analysis or project on-boarding)
  • develop and maintain ‘living’ systematic maps (automatically fetch and classify new publications and integrate into our databases)
  • integrate living synthesis pipelines into human-in-the-loop processes
    (e.g. Cochrane crowd or NACSOS)
  • evaluate and develop automation tools for information extraction
  • help us to unlock multi-lingual evidence synthesis
  • improve our interactive climateliterature.org platform
  • enhance our local database snapshot of OpenAlex with >480M records
  • drive your own ideas that accelerate the evidence synthesis process

Anforderungsprofil:

You are a Bachelor or Master student, enrolled at a German university, and ideally meet the following requirements:

We do not expect you to fulfil all requirements!

  • background in computer science, open-source projects, digital engineering, data science or related fields
  • good software design skills and experience in building and maintaining data processing pipelines and REST-based systems
  • web-based front-end development (esp. typescript, vuejs, webGL)
  • experience (theory & practice) with relational databases (esp. PostgreSQL)
  • strong interest (ideally experience) in information retrieval, data integration, machine learning/AI, LLMs, knowledge graphs
  • excited to use vector databases, e.g. integrating deepset haystack for RAG
  • interested in experimenting with solr, postgres, vector stores, graph databases, knowledge graphs, huggingface
  • interest in data science, clustering, topic models, classification, entity extraction and linking, high-performance compute cluster with high-end GPUs

We will jointly choose tasks based on your expertise and interests. Most important is a strong interest in scientific methods, a solid knowledge foundation (e.g. studying computer science, open source projects) and eagerness to learn. Applicants should reference prior programming experience, ideally linked to specific projects.