Lead Computational Materials Scientist & DFT Expert

Chemstars; Coimbra; Hybrid; EUR 60,000 - 90,000; Full time

Benefits offered by this job

Equity participation

Competitive compensation package

Job summary

Chemstars seeks a seasoned computational materials scientist to lead discovery efforts, designing DFT-based workflows and integrating AI/ML to accelerate screening of crystalline materials. You will collaborate with synthesis and characterization teams to translate predictions into experiments and contribute to a closed-loop discovery engine.

The role requires a PhD and 4+ years in DFT on crystalline materials, with strong Python skills and a track record in automation, high-throughput

Qualifications

• PhD in Physics, Chemistry, Materials Science, or a closely related field.
• Deep hands-on experience with DFT on crystalline materials (4+ years) evidenced by publications or impactful work.
• Experience automating and accelerating DFT workflows (convergence optimization, error handling, high-throughput screening).
• Experience applying AI/ML methods for materials discovery and search.
• Strong Python programming and good practices for reproducible research.

Responsibilities

• Design, implement, and continuously improve DFT-based workflows to predict functional properties of crystalline materials.
• Develop screening strategies to down-select candidates and guide experiments.
• Own computational plans for discovery programs with milestones and deliverables.

Skills

DFT workflows

Python

AI/ML for materials

HPC

Version control

Education

PhD in Physics, Chemistry, or Materials Science

Tools

VASP

Quantum ESPRESSO

GPAW

ABINIT

WIEN2k

CASTEP

ASE

AiiDA

Job description

Chemstars seeks a seasoned computational materials scientist to lead discovery efforts, designing DFT-based workflows and integrating AI/ML to accelerate screening of crystalline materials. You will collaborate with synthesis and characterization teams to translate predictions into experiments and contribute to a closed-loop discovery engine.

The role requires a PhD and 4+ years in DFT on crystalline materials, with strong Python skills and a track record in automation, high-throughput