Computational Chemist | Free Energy Calculations & Solid-State Thermodynamics

If your background is in free energy calculations, thermodynamics of crystalline materials, and advanced solid-state DFT modelling — this is the kind of role where the science actually gets applied.

We’re partnering with a venture-backed scientific software company building next-generation Crystal Structure Prediction (CSP) technology for global pharmaceutical organisations.

This role focuses heavily on thermodynamics, free energy methods, and solid-state molecular modelling within pharmaceutical materials science.

Not drug docking.

Not protein modelling.

Not purely academic research.

This is industrial computational chemistry solving real formulation and solid-state development problems.

What you’ll be doing:

• Apply free energy calculation methods to crystalline molecular systems
• Investigate thermodynamic stability and polymorphic behaviour of solid-state materials
• Run advanced DFT calculations and periodic system modelling
• Work across salts, solvates, hydrates, and co-crystals
• Contribute to the development of next-generation CSP capabilities
• Work closely with senior scientific leadership on technically complex R&D challenges
• Support scientific collaboration with pharmaceutical partners where needed

You’ll need to have:

• PhD (completed or close to completion) in Chemistry, Physics, Materials Science, or related discipline
• Strong understanding of solid-state chemistry and crystallography
• Proven experience applying free energy calculation methods to crystalline systems
• Experience with methods such as:
• Harmonic or quasi-harmonic free energy calculations
• Thermodynamic integration
• Molecular dynamics approaches
• Pseudo-supercritical path methods
• Strong DFT experience, including beyond-GGA functionals such as meta-GGA, hybrid, and dispersion-corrected approaches
• Experience with software such as VASP, Quantum Espresso, ORCA, Gaussian, Turbomole, or Psi4
• Python capability and familiarity with Git

Nice to have:

• Machine learning experience within computational chemistry
• Knowledge of graph neural networks or GPU acceleration
• Experience in polymorph screening or intermolecular potential modelling

The details:

• South Dublin - 4 days onsite
• Healthcare and pension
• Competitive salary package
• Visa sponsorship available

Why this role?

Because this isn’t incremental research.

You’ll be working on hard, unsolved solid-state chemistry problems where computational predictions directly influence how pharmaceutical materials are understood and developed. The work is technical, specialised, and immediately applied — bridging the gap between high-level modelling and real-world industrial impact.

If you want your computational chemistry expertise to actually shape how drugs are formulated and manufactured, this is that kind of environment.

Interested in applying? Take the next step and apply now.