Senior Engineer – Atomistic Simulation R&D

7 days ago


London UK, UK, United Kingdom LoMaRe Technologies Ltd. Full time

Company Description

LoMaRe Technologies is a spin-off from Imperial College London developing novel non-volatile memory (NVM) and sensor technologies with proprietary intellectual property. Our company’s ambition is to commercialise scientific innovation. We are seeking a Simulation Engineer to join our team in London. Join our dynamic and ambitious team to help shape the future of semiconductor chip technology.


Role Description

This role involves developing atomistic and quantum models for novel materials, simulating electronic and magnetic structures, analysing data, and collaborating with experimental teams to optimize device performance. You will also conduct root cause analysis, implement corrective actions, and support transitioning new products into production.


Key Responsibilities:

  • Develop atomistic/quantum models for multi-ferroic tunnel junctions and sensors.
  • Utilize density functional theory (DFT) to simulate electronic and magnetic structures.
  • Apply non-equilibrium Green’s function (NEGF) or Landauer-Buttiker methods for transport property simulations.
  • Analyze numerical data and devise strategies for further simulations or experiments.
  • Extract material and device properties from the atomistic simulations to be used as input of subsequent Technology Computer Aided Design (TCAD).
  • Collaborate with experimental teams to refine material screening and device design.
  • Optimize numerical simulations on Linux systems and ensure efficient use of hardware.
  • Conduct root cause analysis and implement corrective actions.
  • Ensure compliance with all safety policies and procedures.


Qualifications

  • PhD in Materials Science, Solid-State Physics, or related field, or equivalent experience.
  • At least 5 years of experience with DFT electronic structure simulations.
  • Experience with transport simulations, particularly NEGF.
  • Proficiency in analyzing large data sets using scripting.
  • Familiarity with DFT applications in solid-state systems, preferably with Quantum ATK.
  • Experience with transport property computation tools (e.g., Quantum ATK, TranSIESTA).
  • Proficient in Unix/Linux environments and job scheduling software.
  • Ability to develop Python scripts for data post-processing.
  • Strong analytical, problem-solving, and communication skills.
  • Proficiency in Microsoft Office Suite.
  • Ability to work independently and collaboratively within a team.




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