Scientific Modeller (Microscale) - Amsterdam

Job description

Electric Ant Lab (EAL) is seeking a Scientific Modeler (Microscale), to be based in Amsterdam (The Netherlands). This is a real chance to shape EAL’s scientific strategy and to expand upon years of cutting-edge scientific work, which has laid the foundation for our breakthrough R&D digitization tool - RheoCube.

What will your job at EAL look like?

In line with the growth of EAL, we are expanding our Modeling Team. This is the group responsible for building the theoretical frameworks, models, and scalable code around the core tech of our company: RheoCube.

We now seek a Scientific Modeler to join in the molecular-scale side of our team. This will be someone with particularly strong skills in molecular dynamics simulation and statistical thermodynamics. You will be responsible for developing original theoretical ideas and numerical methods for the microscale, implementing these methods into a molecular dynamics context, and optimizing the code to exploit cutting-edge computational technology (e.g. parallel processing, GPU programming, and custom computing architectures).

As one of our newest team members, you will have a passion for creative problem solving. You will show the ability to work autonomously as well as within a team to solve challenging problems.

Responsibilities

  • Development of original theoretical models and numerical methods at the coarse-grained molecular scale

  • Prototyping of models for in-house scientific validation on case studies

  • Implementation of models/methods into a molecular dynamics framework (e.g. in pre-existing packages such as LAMMPS, or in new high-performance code)

  • Testing models for performance, scientific/user robustness, and client usability

About Electric Ant Lab

EAL is a simulation software company located at Amsterdam Science Park. Chemistry-focused R&D scientists at large corporations are a key part of our customer base. Our primary product is RheoCube: a cloud-based virtual lab and simulation platform. It is designed to offer a researcher-friendly alternative to the physical lab approach of trial-and-error, often used for prototyping new products and for applied material research.

Will we be the right fit for you?

EAL is a young company where everybody has the freedom to fulfill their role in a fashion that fits their expertise and way of working. All EAL colleagues (see EAL linkedin) are independent professionals who take pride in applying their expertise to their responsibilities, and collaborate well with colleagues. We offer an open, trusting culture with a fast-paced, dynamic working environment. Of course you will receive a competitive salary and all the practical amenities you'd expect from a workplace in 2022.

About the application process:

  • The process is hybrid, with interviews being held online (although any follow-up interviews could be held at the EAL office depending on the candidate's preference)

  • The process consists of three interview rounds

  • The position is based at the Amsterdam Science Park (Netherlands)

  • Starting date ideally somewhere in the coming months


Special note to Recruiting Agencies and/or recruiters in general: we absolutely do not appreciate any phone calls or cold outreaches with potential candidates. Thank you! We invite ‘your’ candidates to apply themselves.

Requirements

Qualifications

  • PhD (preferable), or MSc plus 6+ years of working experience, in physical chemistry, soft-matter/polymer physics, or related fields.

  • Working knowledge of soft matter physics and simulations

  • Development experience in quantitative molecular dynamics, and in building original simulation algorithms, analysis routines, etc.

  • Strong programming skills, preferably in Python and Fortran.

Optional Qualifications

  • Force-field development & parameterisation.

  • Cheminformatics and applied machine learning

  • Enhanced sampling techniques such as parallel tempering, metadynamics, or path sampling

  • Building frameworks, workflows and data structures from scratch around a computational model.

  • Large-scale simulation and HPC / parallel computing;

  • Collaborative software projects, or development at a simulation software company.