Computational Material Scientist (Phase Change Materials)

August 2019

Bodle Technologies Limited is a University of Oxford spinout developing SRD®, the world’s first solid-state reflective display technology, based on phase-change materials. Providing vivid colour and video-capability, with zero energy use for static image storage, the technology is ideally suited to address the issues of poor outdoor readability and high-power consumption associated with transmissive and emissive displays.   
 
Bodle offers the opportunity to join a small, dynamic team with broad and complementary expertise and an egalitarian ethos. We aim to encourage the brightest minds to work towards achieving our strategic goals and will reward our employees for their contributions with a highly competitive salary, along with the potential for other performance-based benefits including share-options. 
 
We are seeking a Computational Material Scientist with experience in developing new chalcogenide-based Phase Change Materials (PCM) for commercial applications.    
 
The successful candidate will:

a. Design, build, upgrade and maintain computational models of Phase Change Materials for display applications. Examples of material system of interest are GeSbTe, AgInSbTe and many others.

b. Explore, analyse and augment Bodle’s current large experimental database of new and unique PCM materials.  

c. Show initiative and creativity to help achieve ambitious research milestones.

d. Be effective at multitasking.  

e. Be diligent in documenting clearly all activities and results obtained.

f. Be flexible in their willingness to take on projects with different technical elements and timescales, and quick to learn new concepts and techniques.

g. Travel to partner sites in the UK, EU, USA, SE Asia or wherever required based on research, business or commercial needs. Such travel might occur at short notice and urgently. 
 
Other duties 

 
1. If required, supporting the company executives in commercialisation talks, including preparation of reports and creating documents to support the role of technology in potential commercialisation. 
  
2. Assisting with other practical and administrative duties as required. This is a small company, and all staff members are expected to contribute to these tasks 
 
Selection criteria  
 
You should ensure that your letter of application, including your CV and a separate sheet specifically and concisely addressing the following selection criteria, clearly indicates how your experience and qualifications fulfill these requirements, as your application will be judged on that basis.  
 
Essential 
 
1. A good first degree and completed doctorate in theoretical physics, materials science, electronic engineering or related in the following research areas: functional materials, semiconductor science, optoelectronic properties of materials.

2. Atomistic modelling: demonstrate world leading expertise in computational quantum mechanical modelling of Phase change materials. Ability to identify and highlight physical links between material properties and device performance.

3. Teamwork: Interface with the other members of the team (Design, Simulations, Fabrication and Testing) to investigate and correlate results on a daily basis.  

4. Report and documentation: Ability to store and retrieve complete sets of wellstructured, high-quality data from each experiment (conditions, variables, specifications, etc.). Ability to communicate results in an efficient and professional manner is a must.  

5. Evidence of self-motivation and the ability to meet agreed deadlines.

6. Ability to work effectively both independently and as an active member of a team, working cooperatively within the group while effectively planning your own workload within the project.

7. Willingness and ability to travel for short periods to work with collaborators abroad, if required.  

8. A track record of problem-solving and creativity, including patented ideas or published novel research results.  

Desirable  
 
9. Material Informatics: Ability to extract insights and value from existing large databases of experimental and theoretical work. Demonstrate familiarity with Machine Learning techniques applied to material discovery.

10. Experience of collaborations with external groups and industry.

11. Experience with online team management tools (Asana). 
 
 
Bodle Technologies Limited is an Equal Opportunity Employer; employment with Bodle is determined by competence, professionalism and attitude. Gender, race, disability status, marital status, sexual orientation, religion or any other legally protected status do not have any influence on our hiring process or business operations.  
 

For further information please contact:  

Peiman Hosseini (CTO) at pei@bodletechnologies.com

Ben Broughton (VP, Display Technology) at ben@bodletechnologies.com