Postdoctoral Researcher – Large Language Models for Research Data Management in Physics (Physics-LLM)

Your Tasks

Project Overview

The Physics-LLM project is a consortium dedicated to develop an LLM-enhanced Research Data Management (RDM) toolkit based on the FAIR principles. The primary goal is to overcome challenges in data collection, processing, storage, sharing, and finding within the physics domain by leveraging advancements in Natural Language Processing (NLP) and Large Language Models (LLMs).

The project is highly interdisciplinary, uniting researchers from various ErUM communities. The role will focus on developing and deploying LLM-based solutions for metadata extraction, information retrieval, and system interfaces, primarily serving the Astroparticle Physics (APP) and Photon and Neutron (PaN) communities.

Key Responsibilities

The successful candidate will be responsible for contributing to the development and implementation of the following work packages:

LLM-based Information Retrieval

• Establish a foundation for retrieving relevant information from publications and data interfaces in Astroparticle Physics.
  
• Establish controlled vocabularies and knowledge graphs, leveraging LLMs to recognize entities, extract relationships, and semantically enrich data.
  
• Develop mechanisms to convert natural language user queries into structured queries for efficient data retrieval.
  
• Benchmark LLM performance in information retrieval tasks using community-specific datasets.
  
  

  General Contributions
  

• Collaborate closely with team members from DESY, FZJ, and TUM to ensure seamless integration of research outputs across the consortium.
  
• Participate in the development of agentic systems (WP C.1) to enhance workflow design and data analysis reproducibility.
  
• Contribute to the documentation, benchmarking, and publication of project results in high-impact scientific venues.

Your Profile

Required Qualifications

• Education: Ph.D. in Computer Science, Physics, Data Science, or a closely related quantitative field.
  
• Technical Expertise: Strong background in Natural Language Processing (NLP), Large Language Models (LLMs), and related techniques (e.g., Retrieval-Augmented Generation (RAG), fine-tuning, knowledge graph construction).
  
• Domain Knowledge: Familiarity with the data structures, experimental workflows, and publication formats within Astroparticle Physics (APP) and/or Photon and Neutron (PaN) communities is highly desirable.
  
• Software/Systems: Experience with software development, system architecture, and deploying computational models in research environments. Proficiency in relevant programming languages (e.g., Python).
  
• Research Skills: Proven ability to design rigorous experimental methodologies, conduct quantitative benchmarking, and contribute effectively to complex, multi-partner scientific collaborations.
  
• Soft Skills: Excellent communication skills for translating complex technical concepts into actionable insights for diverse scientific audiences.

Benefits: We Have a Lot To Offer

• Regular promotion to the next level and increase in salary pursuant to the collective bargaining agreement for the public service of the German Länder (TV-L) or remuneration pursuant to the Bavarian Public Servants Remuneration Act (BayBesG) plus an additional annual bonus
  
• 30 days annual leave at five working days per week with additional free days on December 24 and 31
  
• Occupational pension scheme and asset accumulation savings scheme

• Excellent support during the academic qualification phase
  
• Thorough onboarding process with a dedicated team
  
• Joint team activities
  
• Place of work within comfortable walking distance of public transport
  
• Family-friendly environment with childcare options, also during school holidays
  
• Flexible working hours
  
• A wide range of training courses and opportunities for professional development
  
• Active health management

Notice

For all job postings, the following applies: Friedrich-Alexander-Universität promotes equal professional opportunities for women. Women are therefore expressly encouraged to apply.

Severely disabled persons as defined by the German Severely Disabled Persons Act will be given preferential consideration if they have the same professional qualifications and personal aptitude and if the advertised position is suitable for severely disabled persons. Details can be found in the respective job posting under “Remarks.”

At the applicant’s request, the Equal Opportunities Officer may be included in the job interview without any disadvantage to the applicant.

All advertised positions are generally suitable for part-time work unless stated otherwise in the job posting.