Jian Xiang Lian

[English]

Ph.D. in applied sciences (quantum chemistry and physics), I am seeking a permanent position in R&D private or public sector. I am passionate about Science and Technology (programming, Data Science, Machine Learning, etc.), and love learning new languages.

[Français]

Diplômé d'un doctorat en sciences appliquées (chimie et physique quantique), je suis à la recherche d'un emploi permanent dans le secteur (privé ou public) de la recherche et du développement. Je suis passionné par les sciences et la technologie (programmation, Data Science, Machine Learning, etc.), ainsi que les langues.

[Español]

Doctorado en ciencias aplicadas (química y física quantica), estoy buscando un empleo en el sector de la investigación y desarollo (privado o público). Soy un apasionado de la ciencias y tecnologías (programación, Data Science, Machine Learning, etc.), y me gusta aprender nuevos idiomas.

Feb 2013 – Dec 2017:  

Ph.D. student and Postdoctoral Associate at the Laboratory for the Chemistry of Novel Materials, University of Mons, Belgium. Computational study of graphene-based electronic device designed via controlled molecular self-assembly at the graphene surface, and the influence of ionic liquid on graphene properties.
My Ph.D. was focused on the study of the self-assembly of organic molecules at the graphene surface, using Molecular Dynamics (MD) simulations. The geometric and electronic properties of ribbon-like graphene structures were also investigated using Density Functional Theory (DFT) and Third-Nearest-Neighbour Tight-Binding methods. I also worked as a Postdoctoral Associate for a year, to investigate the impact of various room-temperature ionic liquids on the electronic
properties of graphene.

Feb 2018 – Sep 2020: 
Postdoctoral Associate at CIC EnergiGUNE, Vitoria-Gasteiz, Spain. Computational study of layered transition metal oxides for Sodium-ion batteries, and mixed oxides for thermochemical energy storage
I worked in the Computational Studies group of Dr. Javier Carrasco and was responsible for the modeling of ionic diffusion in solid-state Na-ion batteries (NIBs), using DFT together with the Nudge-Elastic Band approach. The formation and diffusion of oxygen vacancy in mixed transition metal oxides as a function of the composition were also investigated.
 

To date, I am a Postdoctoral Associate at the Department of Chemistry, University of Calgary, Canada. I am dedicating my research to designing materials for organic solar cells and carbon capture, under the supervision of Prof. Samira Siahrostami. More specifically, my tasks consist in preparing model systems and using computational methods, including DFT and MD, and analyzing data to investigate the physicochemical properties of materials. My responsibilities also include mentoring and assisting students in their research (introducing and teaching new software, thinking, processing, and interpreting results).

During my research, I have used different methods, including Density Functional Theory (VASP, SIESTA), and Molecular Dynamics (BIOVIA Materials Studio, GROMACS) to study atomistic models for various applications (electronic transport devices, supercapacitors, batteries, carbon capture, etc.)

I have developed communication and programming skills (Fortran, Python, Octave), that are essential for my research. Recently, I successfully passed the online course on Machine Learning, with Andrew Ng (Stanford).