Ph.D Student (m/f/d) - AI-Driven Multiscale Modeling for TMD Materials Synthesis and Characterization

This fully funded PhD position is part of the NSF-DFG DMREF project “AI-Driven Platform for 2D Materials Synthesis and Discovery,” an international effort to establish a predictive framework for the synthesis of two-dimensional materials. By integrating computational materials science with autonomous experimentation and artificial intelligence, the project aims to uncover how synthesis conditions govern material formation and use this knowledge to guide the discovery and controlled growth of 2D materials.

The PhD candidate will focus on computational modeling of synthesis and characterization of 2D materials across multiple length and time scales, with a particular focus on transition-metal dichalcogenides (TMDs). The research will combine density functional theory (DFT), ReaxFF reactive molecular dynamics, and machine-learning interatomic potentials (MLIPs) to reveal the mechanisms underlying nucleation, growth, and structural evolution and to develop predictive models that connect atomistic mechanisms with experimentally accessible synthesis conditions.

The position is embedded in a highly interdisciplinary collaboration spanning materials synthesis and characterization, computational materials science, machine learning, and continuum fluid dynamics at the micro- and mesoscales. This environment will allow the candidate to connect fundamental atomistic insight with experiments and larger-scale descriptions of the synthesis environment, developing a broad multiscale and multiphysics perspective on materials growth-from electronic structure and chemical reactions to experimentally observed synthesis processes.

Your responsibilities

• Perform and analyze density functional theory (DFT) calculations relevant to
  TMD-material synthesis and surface processes.
• Conduct reactive simulations using ReaxFF to investigate precursor gas-phase
  chemistry, surface reactions, and growth mechanisms.
• Perform machine-learning interatomic potential (MLIP) simulations and connect
  high-fidelity atomistic calculations with larger-scale models.
• Integrate simulation results with experimental observations and
  machine-learning/data-driven workflows within digital/physical-twin approaches.
• Collaborate with an interdisciplinary international team spanning synthesis
  experiments, computational materials science, AI/data science, and
  continuum fluid dynamics.
• Use national and international HPC resources, including hybrid CPU/GPU systems,
  and develop reproducible workflows for analysis, publications, and presentations.

Your profile

• Bachelor's and master’s degrees in materials science or physics.
• A strong interest in computational modeling of materials and in learning across
  atomistic, data-driven, and continuum-scale methods.
• Prior experience with DFT, reactive molecular dynamics/ReaxFF, MLIPs, atomistic simulation, or related computational methods is highly desirable.
• Background in Programming skill using such as Python, MATLAB, or C++, and
  familiarity with Linux/Unix environments and high-performance computing (HPC)
  systems is advantageous.
• Effective communication skills, both written and verbal in English, are essential
  for presenting research findings and collaborating with team members.
• A genuine enthusiasm for contributing to cutting-edge research in the field of
  materials science.
• A self-motivated personality with a strong curiosity for working in a multi-disciplinary
  team environment on scientifically challenging problems. Team-oriented with the
  ability to collaborate effectively with others.

Position and salary

This position is available immediately. Salary and benefits are according to the Treaty for German public service (TVöD Bund) to a level of E13 (75%), taking work experience and special professional skills into account.

What we offer

• Supportive environment with experts for various scientific sub-fields.
• Modern office located in the heart of Berlin with excellent public transport
  connections and a subsidized travel ticket.
• Access to national and international HPC centers with modern hybrid CPU/GPU
  architectures.
• International and culturally diverse community.
• Close collaboration with a nationa/international team integrating experiments,
• computational materials science, machine learning, data science, and
• micro- to mesoscale continuum modeling.

What we offer

• Unique theory/simulation capabilities
• Access to national and international HPC centers with modern hybrid CPU/GPU architectures.
• Supportive environment with experts for various scientific sub-fields.
• International and culturally diverse community.
• Location in the heart of Berlin with excellent public transport connections and a subsidized travel ticket.
• Close collaboration with a national and international team integrating experiments, computational materials science, machine learning and data science as well as micro- to mesoscale continuum modeling.

About PDI:

The Paul Drude Institute is part of the Forschungsverbund Berlin e.V. and a member of the Leibniz Association. We are a globally recognized research institution
specializing in the development of novel functional materials through molecular beam epitaxy. The institute carries out basic and applied research at the nexus of materials science, condensed matter physics, and device engineering.

Inclusive and equal opportunity employer

With approximately 100 employees and more than 15 nationalities, PDI is committed to building a talented, inclusive, and culturallydiverseworkforce. We understand that our shared future is guided by basic principles of fairness and mutual respect.

As an equal opportunityand family-friendly employer, we offer highly flexible employment conditions, such as flexible working hours, parental leave, and
home office, and we strive to create a family- and life-conscious working environment.

Among equally qualified applicants, preference will be given to candidates from marginalized groups. That means, we welcome every qualified application, regardless of sex and gender, origin, nationality, religion, belief, health and disabilities, age or sexual orientation.

PDI follow our gender equality plan, so we want to engage women* to apply at PDI to balance the gender ratio in science. Disabled applicants with equal qualification
and aptitude will be given preferential consideration.

How to apply

Please send your application as a single PDF file to Susanne Sawert (she/her) at recruiting@pdi-berlin.de by Sept 30, 2026, with the title of the position in the subject line. The document should include:

• a dedicated cover letter
• CV
• publication list (if exists)
• contact information of two references (if exists)
• diploma(s)
• notes transcript(s)