Call for Postdoctoral Fellows

Join the Double Layer lab-hub as a postdoctoral fellow at the University of Latvia!

If you are a post-doc seeking independence through training skills and gaining knowledge in a supportive environment, then this post is for you. This is an opportunity to advance your career through Marie Skłodowska-Curie Actions’ (MSCA) by focusing on competencies, like academic writing, research methods, and supervision, that are essential for succeeding in academia or industry.

I suggest submitting one 10 page-long proposal to at least three calls on the 10 September 2025. The core application is for the MSCA postdoctoral fellowship which provides funding for up to 24 months of research and training. To get this prestigious grant one must gain more than 95% in the evaluation, yet passing the 85% threshold already opens the opportunity to be funded by the ERA Fellowships. Moreover, passing the 70% threshold makes you eligible to be funded by Latvia. Even more, there is a Latvian post-doc fellowship. Submitting to all these calls increases your chances to fulfill your research idea and advance your career. These fellowships include a salary (up to 3000 € net for MSCA in Latvia), research expenses, and, if applicable, family allowance.

CallSubmissionDecisionStartThresholdSuccessLink
Latvian 1May 2025Summer 2025Sept 2025…50%lzp.gov.lv
MSCASept 2025Feb 2026Mar–Dec 202695%16%, 1700PFec.europa.eu
ERA TalentsSept 2025Feb 2026Mar–Dec 202685%20PFec.europa.eu
Latvian 2March 2026May 2026Jun–Dec 202685%–lzp.gov.lv

Why University of Latvia?

  • Great working conditions at a new campus (house of nature) in the heart of Riga.
  • Work-week of 40 hours from Monday to Friday and vacation.
  • Attention to work–life balance, safety, and DEI.
  • Systematic support during the process of application.

Why the Double Layer lab-hub?

  • Double Layer lab-hub is a place for modelling scalable chemical processes involving the electrical double layer.
  • It has a horizontal hierarchy and focuses on process-orientated research with attention to excellence and collaboration.

Why Vladislav Ivanistsev as a mentor?

  • Research experience related to the electrical double layer, see list of publications.
  • Experience in supervising dozens of postdocs and BSc–PhD students as well as mentoring over 100 members of the Estonian national team at the international Chemistry Olympiad.
  • Experience in obtaining MSCA PF and national grants.
  • Personal support during the process of application.

Further details

To be considered for the opportunity, you will undergo a pre-selection process based on your CV, project idea, and motivation letter. There are three main eligibility requirements:

  • You must hold a PhD and up-to 8 years of full-time research experience by the time of the application. Check the eligibility calculator.
  • Applicants of any nationality are welcome, but they must not have lived or worked in Latvia for more than 12 months during the 3 years leading up to the closing date of the call on 10 September 2025.
  • Applicants must choose the Chemistry Department at the university of Latvia as their host institution.

For any other further questions, please contact vladislav.ivanistsev@gmail.com

Uniting “simulants” over pizza

This semester I am co-organising a seminar on computer simulations (3 ECTS, LOTI.05.076). One of the aim is to gather and unite researchers from different institutes. Our common topic is using computers in research, so we are “simulants”, i.e. simulating reality via calculations. Some of core organisers are pictured in the centre, from left to right: Taavi Repän, Tauno Tiirats, Veronika Zadin, and Juhan Matthias Kahk.

My first talk was about running simulations on HPC, e.g. using apptainers. Probably because of free pizza there were two–three dozen of participants from institutes of Chemistry, Physics, and Technology, which is a surprisingly high number for the university of Tartu. It is a great start and I am looking forward to contribute more into strengthening collaboration between the institutes.

Colors in ASE

Updated colors for atoms in ASE in 2024 look like this:

For POV rendering there are several options: ASE2, ASE3, Glass, Glass2, Intermediate, JMOL, Pale, Simple, VMD. I like intermediate because it does not have an reflection and glare.

List of banned tells for GPT

1) Just watched Andy Stapleton youtube-video about echo technique for working with chatGPT. After that I have made my list of banned tells for GPT. Here it is.

Vibrant, Bustling, Vital, Out of the box, Underscores, Dive into, Reverberate, Delve, Hustle and bustle, Foster, Labyrinthine, Moist, Remnant, Nestled, Game changer, Symphony, Gossamer, Enigma, A testament to, Indelible, Meticulous, Meticulously, Navigating, Complexities, Realm, Understanding, Shall, Tailored, Underpins, Everchanging, Ever-evolving, Not only, Embark, Designed to enhance, It is advisable, Daunting, When it comes to, In the realm of, Amongst, Unlock the secrets, Unveil the secrets, Diving, Unleash, Harness, Tapestry, In summary, Take a dive into, Analogies to being a conductor or to music, Metropolis, Unless, Arguably, Ultimately, To put it simply, Promptly, In today's digital era, Subsequently, Leverage.

2) Previously I also used this prompt for working with LaTeX codes, but now I simply use texGPT in overleaf for quick drafting.

Start every sentence on a new line. Add line breaks after every 60 characters to make the text easier to read, but do not add these breaks within commented text. Preserve all original comments exactly as written, and do not delete anything unless explicitly instructed. Use British English and simple language, avoiding words that non-native speakers may not understand. Avoid typical ChatGPT phrases like "leveraging" or any overuse of sophisticated words, adjectives, or jargon. Do not use gerunds or adjectives excessively. Maintain the accuracy of content and avoid changes to technical terms.

3) When working within a project, I define instructions like this:

Prohibited words and phrases: I must avoid the following words and phrases, along with their derivatives: However, Additionally, Vibrant, Bustling, Vital, Out of the box, Underscores, Dive into, Reverberate, Delve, Hustle and bustle, Foster, Labyrinthine, Moist, Remnant, Nestled, Game changer, Symphony, Gossamer, Enigma, A testament to, Indelible, Meticulous, Meticulously, Navigating, Complexities, Realm, Understanding, Shall, Tailored, Underpins, Everchanging, Ever-evolving, Not only, Embark, Designed to enhance, It is advisable, Daunting, When it comes to, In the realm of, Amongst, Unlock the secrets, Unveil the secrets, Diving, Unleash, Harness, Tapestry, In summary, Take a dive into, Analogies to being a conductor or to music, Metropolis, Unless, Arguably, Ultimately, To put it simply, Promptly, In today's digital era, Subsequently, Tailored, and Leverage. 
I must avoid using "potential" in the sense of showing the capacity to develop into something in the future, because "electric potential" is a variable in Vlad's research. I must avoid "framework" in the sense of a basic structure underlying a computations, because "organic framework" is a material in Vlad's project.  I must avoid using "capacity" and "capacitance" in sense of ability to do something, because similar terms are used in electrochemistry.

Faculty interview

Recently I have been preparing for an interview for a faculty position. As usual I watched a lot of videos, read some tutorials, chatted with GPT, and talked to people (to whom I am very grateful).

The most insightful video turned out to be by Wenhao Sun UM. See below. It is about having a solid research vision!

Besides I would highly recommend a youtube channel “Life in academia” of a very positive prof. Matthias Rillig.

P.S. Despite preparation, I have not anticipated even a single question.

My first presentation generated with AI

I am working on a presentation and use AI for the first time to draft some texts.

There are already existing solutions. Like plug-ins for google slides and copilot that works with powerpoint. I am using chatGPT and work in google slides.

Here is how I add some slides through app scripts:

function addSlide() {
    const presentationName = "ScientificActivities";
    const presentations = DriveApp.getFilesByName(presentationName);
    if (!presentations.hasNext()) return;

    const presentation = SlidesApp.openById(presentations.next().getId());
    const layouts = presentation.getMasters()[0].getLayouts();
    const targetLayout = layouts.find(layout => layout.getLayoutName() === "OBJECT");
    if (!targetLayout) return;

    const titleText = "Bridging Modelling and Scalable Chemical Processes"; // Edit title here
    const bodyText = "Assoc. Prof. Vladislav Ivaništšev"; // Edit body content here

    const newSlide = presentation.appendSlide(targetLayout);
    newSlide.getPlaceholder(SlidesApp.PlaceholderType.TITLE).asShape().getText().setText(titleText);
    newSlide.getPlaceholder(SlidesApp.PlaceholderType.BODY).asShape().getText().setText(bodyText);
}

Title and body can be generated by … within a long conversation with my personal research assistants. I enjoy the process because these skills will save me a lot of time in the future, although right now it took me some hours to get this simple code working. I have also used AI to find and download a dozen on logos of universities that I have visited (shown below). And it saved me time to get facts from my CV right into the slides.

Setting infrastructure is the first step

This week, I have repeatedly discussed the same topic with many peers: What is the first step in starting a new project? Like … a PhD project. For me, it’s about lowering the barriers that prevent beginning the research in the first place. It is all about setting up the right environment, which I call “infrastructure.”

Sometimes, my infrastructure gets disrupted, which slows me down. For example, my new laptop was a major annoyance for some months already. The fan was running at 100% RPM constantly after a software update. It made me worry instead of focusing on the work. Finally, this Saturday morning, I managed to fix it. I am not sure which solution worked – perhaps it was “fan control” – but now I can calmly work in silence.

Additionally, while troubleshooting, I learned more about my CPU and GPU setup. Interestingly, my laptop has two types of CPUs (performance and efficient), totalling 10 cores and 12 threads. I added commands for GPAW Python to run my DFT calculations on 4 and 8 threads accordingly. Yes, I enjoy running tests on my laptop before syncing them via Git and running them on an HPC. Also, I have finally set up the second build-in SSD to store large amounts of data. Hurray!

alias gw8="taskset -c 4-11 mpirun --use-hwthread-cpus -np 8 --bind-to core python"
alias gw4="taskset -c 0-3 mpirun --use-hwthread-cpus -np 4 --bind-to core python"

Calculations run twice faster in 4 performance threads than in 8 efficiency ones!

Feels so good when an infrastructure works for you (and not the other way around).

P.S. The problem returned in a while. This time I installed ProcessLasso to set CPU affinity of most of the processes to energy efficient CPUs.

Optimizers in ASE

Optimising even simple intermediate on metal surfaces might be tricky. They tend change the adsorption site. OOH also very flexible in changing geometry. Thus, some optimizers get stuck (like BFGSLineSearch) while others just crush (like GPMin).

Here is my test with OCPCalculator and EquiformerV2-31M-S2EF-OC20-All+MD (on 1 CPU in Google Colab). Optimisation of OH on Pt(111) is simple.

Here SciPyFminBFGS failed and other optimizers ended up with the same structure, shown below.

Optimisation of OOH on Pt(111) is challenging. GoodOldQuasiNewton, FIRE, FIRE2, MDMin, and BFGSLineSearch (QuasiNewton) do not converge in 95 cycles (which I set as a maximum number of cycles). GPMin, SciPyFminBFGS, SciPyFminCG, and LBFGSLineSearch failed.

Geometry obtained with FIRE2 (similar to BFGS and FIRE)
Geometry obtained with LBFGS. It is clearly far from the optimum.

ResearchCOMP – the European Competence Framework for Researchers

The new Framework for Researchers is a cool tool for planning your career. However, it is so hard to understand and remember. That is why I suggest using the following tree analogy.

ResearchCOMP is an essence like a tree. Roots of critical thinking (1) with trunk of self-management (2) and branches of collaboration (3) hold leaves as research (4) and fruits as impact (5). Water = management 6) and sun = tools (7) nourish the research tree.
The following illustration has been prepared by my son:

Art created by Naran Pavanello, 9 years old

ResearchCOMP, Like a Tree

Roots of critical thinking, deep and strong,
The trunk of self-management keeps you moving along.
Branches of collaboration, reaching far,
Leaves of research, showing who you are.

Fruits of impact, growing bright,
Water of management keeps it right.
Sunlight from tools makes it thrive,
Nourishing the research, keeping it alive.

“Content created with assistance from ChatGPT, an AI language model by OpenAI.”

With this analogy it is now easy to explain what a PhD. student should focus on.

Cognitive Abilities (Roots):
As a Ph.D. student, you first build your thinking skills like problem-solving and creativity. These skills are like roots that hold you on the ground.

Self-Management (Trunk):
You need to manage your time and stress, set goals, and balance your workload. This helps you stay focused and handle challenges, like a trunk.

Working with Others (Branches):
Collaboration is key. Branch with supervisors and teams, seek feedback, and build connections to grow your research.

Managing Research (Water):
You manage your PhD project. This includes organizing resources, meeting deadlines, and planning your work. It is like a flow.

Managing Research Tools (Sun):
Learn to use research tools like data management and software. These help keep your work organized. It is like external source of energy = sunlight.

Doing Research (Leaves):
This is your core work – running experiments, analyzing data, and writing papers to build expertise in your field. Leaves are as dynamic as your research.

Making an Impact (Fruits):
Your research creates impact. Publish, attend conferences, and share your findings as fruits to the society.

And now you can compare a young tree to a mature one. The difference is that the young one is expected to “bloom”, whether the mature one is expected to give “fruits”, as illustrated below.

Working with cubes

Working with cubes can be tedious. I need to show a change in electronic density of a MOF. For that I made two cubes for neutral and charged MOF. Then took their difference using cube_tools, like this.

import numpy as np
from cube_tools import cube

# Load the cube files using the cube class
cube1 = cube('mof_opt_0.0.cube')
cube2 = cube('mof_opt_2.0.cube')

# Subtract the data from cube1 from cube2
cube_diff = cube('mof_opt_2.0.cube')
cube_diff.data = cube2.data - cube1.data

# Get z-axis data and find indices where z > 13.3 (jellium density)
z_indices_above_threshold = np.where(cube_diff.Z > 13.3)[0]

# Remove densities above z = 13.3 by setting them to zero
for idx in z_indices_above_threshold:
    cube_diff.data[:, :, idx] = 0

# Save the modified cube data to a new file
cube_diff.write_cube('cdd.cube')

Once I have got the charge density difference and opened it in VMD, I realised that one part of my MOF is right at the border of a periodic cell, so that part of density was split. So, I used a terminal command to shift the cube like this “cube_tools -t -24 -36 0 cdd.cube”. I had to shift manually positions of the atoms by taking into account the voxels size. Next challenge was hiding half of my MOF to clear the view. So I used this tcl syntax in VMD:

vmd > mol clipplane normal 0 0 0 {1 0 0}
vmd > mol clipplane center 0 0 0 {3 0 0}
vmd > mol clipplane status 0 0 0 1
vmd > mol clipplane normal 0 1 0 {1 0 0}
vmd > mol clipplane center 0 1 0 {3 0 0} 
vmd > mol clipplane status 0 1 0 1
vmd > mol clipplane normal 0 2 0 {1 0 0}
vmd > mol clipplane center 0 2 0 {3 0 0}
vmd > mol clipplane status 0 2 0 1

Here is the result – density is almost homogeneously spread over my MOF upon charging.