Open positions for PhD and master students in the lab of T. J. Jacobsson at Nankai University
Research direction
Utilization of automation and artificial intelligence for closed loop experimentation to accelerated development of energy materials, like perovskite solar cells.
Open positions
There are now open positions for PhD and master students to join the Jacobsson lab.
Are you interested in material science and materials for energy applications?
Are you curious about developing your skills in programming and applied artificial intelligence?
Would you like to work with lab automation for accelerating materials science?
Do you have a background in chemistry, physics, computer science, or in related subjects?
Then this could be the right place for you. If you are interested, please send an email to Jacobsson.jesper.work@gmail.com
About the research in the Jacobsson group
The main theme for the Jacobsson lab is closed loop experimentation for accelerated development of material research. This direction is born out of a frustration with the slowness and inefficiency of material discovery and development in combination with a belief that it can be done much better. By utilizing recent developments in artificial intelligence and automation, I think there is a potential to reform much of what we do in material science and bring the field up to a completely new standard in terms of output and research efficiency. The way we will tackle this problem in the Jacobsson lab is a three-stage process.
The first step is lab automation of high throughput combinatorial synthesis and characterisation utilizing flexible robots. The philosophy is that robots are better than humans at doing large amounts of repetitive lab work in a consistent way, like mixing solutions, deposition of thin films, and routine characterisation. From a practical perspective, this involves building, assembling, and programming equipment for automating standard procedures, and do this in an affordable and generalisable way.
The second step involves closing the experimental loop by adding a layer of artificial intelligence to the lab automation. This means including evaluation and decision capacity using for example Bayesian optimisation, genetic algorithms, reinforcement learning, and neural networks to guide and set up the next round of experiments on the fly. The idea is that the robotic system synthesises and characterise a sample, after which the data is analysed automatically. Based on the new data, the research objective, and the boundary conditions, the algorithms can then on the fly guide the robotic system how to set up the next experiment in order to maximise the insight towards reaching the objective. The overarching goal is to create procedures, protocols, and open-source code that enables autonomous robots for high-throughput synthesis and characterisation in combination with AI-driven automated decision capacity.
The third step involves using this AI-driven automation to accelerate materials research. The primary target here will be halide perovskites for solar cell applications and other energy relevant materials. Examples of research questions involve development of perovskite-perovskite tandem cells, solution processed electron selective contacts in pin-architectures, exploring lead free perovskites, and navigating the chemical space during compositional engineering.
Work tasks
The work will include things like:
Developing automated lab procedures. We will as far as possibly use commercial robot systems, but we will need to do some modification and developments to suit our needs.
Prepare chemicals and stock solutions.
Conduct control experiments in terms of synthesis and thin film deposition.
Implementation of automated routines for data analysis and algorithms for AI-driven experiment planning, execution, and evaluation.
Writing python code
Material characterisation, e.g., UV-vis, Photo luminescence, XRD, SEM, XPS, Electrochemistry, etc.
Data analysis
Keeping up to date with the literature
Writing papers
The exact focus and content of your projects will depend on your interests and skills.
Qualifications
Background in chemistry, physics, materials science, data science, or related subjects.
I do not speak Chinese which means that good English communication skills are required.
Some basic programming experiences.
Knowledge in python is a plus.
Previous work with solar cell materials and material characterisation is a plus.
I am looking for talent wherever I may find it. If you are interested, talented, and ambitious, and think you may fit in the group, please apply even if your background is somewhat outside the stated requirements.
How to apply
If you are interested, send an email to Jesper Jacobsson (Jacobsson.jesper.work@gmail.com) with your CV and a personal letter. Candidates with interesting CVs will be invited for an online interview. Candidates that perform well on the online interview will be invited to send in a formal application to the university for starting a PhD in the spring term 2023. Anyone that gest accepted by the university are welcome to do their PhD in the Jacobsson group.
For more information about the University’s application process and how to apply, please see (https://ceo.nankai.edu.cn/info/1099/3029.htm)
The last day to apply to the university to start during the spring 2023 is by the beginning of November.
About T. J. Jacobsson
Jesper Jacobsson obtained a PhD in Inorganic Chemistry at Uppsala University, Sweden, in 2014 with a project focusing on ZnO quantum dots and CIGS-based devices for solar hydrogen production. After his PhD, he has worked as a postdoc at EPFL in Switzerland, Cambridge University in UK, Uppsala University in Sweden, and at Helmholtz Zentrum Berlin in Germany. He has also worked as a research engineer at Evolar AB. During his postdoc time he has worked with various aspects of perovskite solar cells including device engineering, tandem integration, data management, and advanced material characterization. From December 2021, he is employed as a professor at Nankai University in the College of Electronic Information and Optical Engineering. He is there building a group focused on exploring how to utilize automation and artificial intelligence to improve research in energy materials. The group does at the moment contain 5 persons and is growing.
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