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

About the position

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

About the position

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).

research will combine density functional theory (DFT), ReaxFF reactive

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,

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

synthesis processes.

Your responsibilities

Conduct reactive simulations using ReaxFF to investigate precursor gas-phase

and develop reproducible workflows for analysis, publications, and presentations.

Bachelor's and master’s degrees in materials science or physics.

A strong interest in computational modeling of materials and in learning across

Prior experience with DFT, reactive molecular dynamics/ReaxFF, MLIPs, atomistic simulation, or related computational methods is highly desirable.

for presenting research findings and collaborating with team members.

A genuine enthusiasm for contributing to cutting-edge research in the field of

Position and salary

This position is available immediately.

Salary and benefits are according to the

experience and special professional skills into account.

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.

We are a globally recognized research institution

specializing in the development of novel functional materials through molecular

The institute carries out basic and applied research at the nexus of materials science,

Inclusive and equal opportunity employer

As an equal opportunity and family-friendly employer, we offer highly flexible

PDI follow our gender equality plan, so we want to engage women* to apply at

(she/her) at recruiting@pdi-berlin.de by Sept 30, 2026, with the title

of the position in the subject line.

Deadline: 2028-09-15T08:15:52.647+02:00

Salary: {"@type":"MonetaryAmount","currency":"EUR","value":{"@type":"QuantitativeValue","minValue":4411,"maxValue":4411,"unitText":"MONTH"}}

What you’ll bring

• Bachelor's and master’s degrees in materials science or physics.
• Prior experience with DFT, reactive molecular dynamics/ReaxFF, MLIPs, atomistic simulation, or related computational methods is highly desirable.
• Disabled applicants with equal qualification
• Analyze complex simulation and experimental datasets; experience with
• Mentor Master’s/PhD students in computational techniques, model development,
• HPC Expertise: demonstrated experience with high-performance computing,

At a glance

Position type

PhD, Postdoc

Institution

Paul Drude Institut Berlin

Department

Not stated

Research group

Not stated

Location

Berlin, Deutschland

Supervisor / contact person

Prof. Nadire Nayir

Funding

Fully funded
This fully funded PhD position is part of the NSF-DFG DMREF project
Position and salary
Salary and benefits are according to the
Salary: {"@type":"MonetaryAmount","currency":"EUR","value":{"@type":"QuantitativeValue","minValue":4411,"maxValue":4411,"unitText":"MONTH"}}
{"@type":"MonetaryAmount","currency":"EUR","value":{"@type":"QuantitativeValue","maxValue":4411,"minValue":4411,"unitText":"MONTH"}}

Duration

Not stated

Expected start

Not stated

Vacancy reference

https://paul-drude-institut.softgarden.io/#organization

Research focus

Discipline

Materials Science, Chemistry, Physics

Research area

Not stated

Methods

DFT, Molecular dynamics (MD), Continuum modeling, Synthesis

Software

Python, MATLAB

Dates to know

Listed on FOSS Positions

17 Sep 2026

Original advertisement date

2026-09-15

Application deadline

15 Sep 2028 · 06:15 UTC

Priority review date

Not stated

Last checked

17 Sep 2026

Last updated

17 Sep 2026

2028-09-15T08:15:52.647+02:00

How to apply

marginalized groups. That means, we welcome every qualified application, regardless
PDI follow our gender equality plan, so we want to engage women* to apply at
How to apply
Please send your application as a single PDF file to Susanne Sawert

Contact: recruiting@pdi-berlin.de

Original sources

https://paul-drude-institut.softgarden.io/job/67338840?l=en ↗

https://paul-drude-institut.softgarden.io/job/67336495?l=en ↗