PhD Fellowship position in Designing Solid Electrolytes for Li- and Na-ion Batteries using Deep Learning-based Models (DeepSolo)

The Department of Mechanical, Electrical and Chemical Engineering at the Faculty of Technology, Art and Design (TKD) has a vacant PhD Fellowship position in Designing Solid Electrolytes for Li- and Na-ion Batteries using Deep Learning-based Models (Deep-Solo).

Area of research

Currently, liquid electrolyte-based batteries are the most used batteries in portable devices and electric vehicles. However, the liquid electrolytes used in these batteries, which are based on organic solvents, pose a significant safety risk due to their potential for leakage and combustion. Solid-state electrolytes (SSEs) are safer alternatives to liquid electrolytes, as they offer improved electrochemical stability and are non-flammable. SSEs also allow for the use of Li and Na metals as the anode, thus increasing the energy density of Li- and Na-ion batteries. Furthermore, SSEs can be stacked in multiple layers to enhance energy density further, making them promising candidates for the next generation of electrolyte materials to replace liquid electrolytes. 

Developing a single material that meets all the requirements for a suitable SSE is challenging. On the one hand, achieving a non-toxic and stable SSE with high ionic conductivity requires the use of ceramic-based conductors. On the other hand, a material with low charge transfer resistance at the solid electrode-electrolyte interface needs a soft material such as a polymer-based electrolyte. Combining hard and soft materials (e.g., polymers and ceramics) into a single polymer nanocomposite solid electrolyte (PNSEs) can be a promising approach to address this material paradox. PNSEs can enable achieving desirable properties, including high ionic conductivity, low interface resistance, enhanced mechanical properties, and superior electrochemical stability. 

Concerning the small-scale effects on the material behavior of PNSEs, only molecular simulations can provide a systematic method to understand the relationship between the structure and function of the complex systems and accelerate the development of more high-performing PNSEs. The ultimate goal of the DeepSolo project is to develop, implement, and validate novel deep-learning models for molecular dynamics and coarse-grained simulations for the characterization, design, virtual testing, and optimization of PNSEs for Li and Na-ion batteries. 

Qualification requirements and conditions

• Master's degree within in engineering, physics, or applied mathematics. The degree must contain 120 credits (ECTS). All exams for the master's degree must be completed by 30 June 2025.
• An academic profile that suits the research group's and the department’s needs.
• Good communication skills in English, oral and written.

The following grade requirements are a condition for employment in the position:

• Minimum average grade B on subjects included in the master's degree.
• Minimum grade B on the master's thesis.

Admission to the Engineering Science within three months of employment is a prerequisite for the position. If you already have a doctorate in a related field, you will not qualify for the position.

In assessing the applicants, emphasis will be placed on the department's overall needs and the applicant's potential for research within the field.

General criteria for appointment to recruitment positions are set out in the Regulations relating to terms and conditions of employment for positions such as postdoctoral fellow, research fellow, research assistant and specialist candidate (FOR-2006-01-31-102), cf. transitional rules described in Section 13.2 of the Regulations relating to the Act relating to Universities and University Colleges.

Preferred selection criteria

It is an advantage if you have:

• Experience with advanced simulation techniques for materials research, such as molecular dynamics, coarse-grained modeling, Monte Carlo, or quantum methods.
• Knowledge of machine learning models applied to material modeling.
• Proficiency in programming languages, such as Python, MATLAB, Julia, and C++, or molecular dynamics programs, such as LAMMPS, to predict mechanical/electrical properties of materials.
• Knowledge/experience in advanced battery technologies or related energy storage systems.

Preferred personal skills:

• Ability to work independently, take initiative, plan, dimension and direct own work.
• Capacity to conduct and report research in a structured, analytical and ethical way
• Good communication and presentation skills
• Strong motivation for doctoral studies, and ability to perform critical analysis as well as possessing good levels of cooperative and communicative abilities.

Personal suitability will be emphasised.

It is important to OsloMet to reflect the population of our region, and all qualified candidates are welcome to apply. We make active endeavours to further develop OsloMet as an inclusive workplace and to make adaptations to the workplace where required. You are also welcome to apply for a position with us if you have had periods where you have not been in employment, education or training.

We can offer you

• An exciting job opportunity at Norway’s third largest and most urban university
• Opportunities for professional development
• Beneficial pension arrangements with the Norwegian Public Service Pension Fund (spk.no/en/)
• Beneficial welfare schemes and a wide range of sports and cultural offers
• Free Norwegian language classes to employees and their partners/spouses
• Workplace in downtown Oslo with multiple cultural offers

Practical information about relocation to Oslo and living in Norway.

Application

To be considered for the position, you must upload the following documents by the application deadline:

• Application letter describing your motivation and how your professional profile is relevant for this position.
• Copies of diplomas and transcripts for bachelor's and master's degrees (which list subjects and grades) and certificates. Please note that a description of the grading system at the university/country where you took your degree must be attached. This must be an official document from your university. Foreign diplomas must be translated into English by the university that issued the diploma.
  
  • o   Your master's degree must be completed at the time of application. If you have not received a diploma before the application deadline, you must attach a preliminary transcript in English or a Scandinavian language from your university by the application deadline, in addition to an official confirmation from the educational institution that all examinations for the master's degree, including the master's thesis, have been completed. Official diploma and transcript must be forwarded by the joining date.
• Name and contact information of two references (name, relationship, e-mail and telephone number).
• Scientific work that you want to be assessed.
• Applicants from countries where English is not a first language must submit the result of an official language test. The following applicants are exempt from this language requirement:
  • Applicants from EU/EEA countries.
  • Applicants who have completed at least one year of study in Australia, Canada, Ireland, New Zealand, Great Britain or the United States.
  • Applicants who hold an “International Baccalaureate (IB)” diploma.
    
    The following language tests are approved documentation: TOEFL, IELTS, Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). In these tests, you must have achieved at least the following scores:
  • TOEFL: 600 (paper-based test), 92 (Internet-based test)
  • IELTS: 6.5, where none of the sections should have a lower score than 5.5 (only the Academic IELTS test is accepted).

Official diploma and transcript must be submitted before taking up the position, no later than 01.10.2025. If your educational institution is not able to deliver an official diploma by the deadline, you must submit documentation from the institution that confirms that your master´s degree is completed by the same deadline.

We only process applications sent via our electronic recruitment system and all documents must be uploaded wihtin the deadlines stated in the announcement text for your application to be processed. The documents must be in English or a Scandinavian language. Translations must be authorized. You must present originals at any interview. OsloMet checks documents, so that you as a candidate will get a real evaluation and fair competition.

Other information

If you would like more information about the position, feel free to contact:

• Head of Research, Biplab Kumar Datta, biplab.datta@oslomet.no, +47 672 37 290
• Associate Professor Behrouz Arash, behrouz.arash@oslomet.no, +47 672 36 011

The position is paid according to the pay scale for Norwegian state employees, position code 1017 PhD fellow, NOK 532 200 per year.

If you have documents that cannot be uploaded electronically, please contact hrtkd@oslomet.no. 

If you would like to apply for the position, you must do so electronically through our recruitment system.

Deadline for applications: 01.05.2025
Ref.: 25/03201