Projects per year
Personal profile
Personal Statement
I obtained my PhD in Nanophysics and Photonics from the University of Grenoble Alpes, under the supervision of Prof. Didier Mayou and Prof. Asghar Asgari. My doctoral research focused on “Nonequilibrium Modelling of Solar Cells: Quantum Effects at the Nanoscale Level.” During my PhD, I also joined the group of Prof. Matthias Ernzerhof at the University of Montréal as a Visiting Scholar, where I was introduced to quantum chemistry through one of the leading scientists in the field.
Driven by my interest in cross-disciplinary and multi-methodology research, I then joined the group of Prof. Alessandro Troisi at the Materials Innovation Factory, University of Liverpool, as a Postdoctoral Research Associate, working on “Computer-Aided Materials Discovery.” During my postdoctoral career, I was the first to demonstrate the feasibility of high-throughput virtual screening by combining chemical databases with advanced physical models. This work became an important foundation for the DiaDEM Materials Discovery Platform (https://www.diadem-project.eu/).
A defining milestone in my journey was being recognised through the L’Oréal–UNESCO For Women in Science Rising Talents Award, which celebrates women researchers whose work advances scientific knowledge and contributes to addressing global challenges. For me, this recognition was a powerful encouragement to keep pushing boundaries and to continue developing research that connects fundamental science with real-world impact.
In December 2022, I started a new chapter at the University of Strathclyde as a Chancellor’s Fellow in Materials and Computational Chemistry, within the Department of Pure and Applied Chemistry.
Research Interests
I am a theoretician specialising in the development of methods that combine novel physical models with computational screening to identify advanced materials with targeted properties, determine the realistic physical limits to such properties, and drive practical materials (inverse) design strategies. Currently, my research is focused on:
- Computational discovery and design of functional molecules and materials
- Charge transport properties of molecular semiconductors
- Optical properties of organic molecules and solids
- Crystal structure prediction of rigid conjugated molecules
Expertise And Capabilities
- Developing Physical Models
- Theoretical and Computational Chemistry
- High-Throughput Virtual Screening
- Data-Driven Materials Discovery
- Materials Design Strategies
Academic / Professional qualifications
Certified Mental Health First Aider (MHFA England)
Education/Academic qualification
Postgraduate Certificate in Learning and Teaching in Higher Education (PGCLTHE), University of Strathclyde
Award Date: 20 Sept 2024
Doctor of Philosophy, University of Grenoble Alpes
2014 → 2017
External positions
Honorary Research Associate, University of Liverpool
26 Dec 2022 → …
Keywords
- Semiconductors
- Materials Chemistry
- Charge Transport
- Optical Properties
- High Throughput Screening
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- 1 Similar Profiles
Collaborations and top research areas from the last five years
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Accelerating Crystal Structure Prediction for Organic Semiconductors through Motif-Constrained Search
Nematiaram, T. (Principal Investigator)
30/10/25 → 29/10/26
Project: Research
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Industrial Case Account - University of Strathclyde 2023 | Myasnikov, Nikita
Tuttle, T. (Principal Investigator), Nematiaram, T. (Co-investigator) & Myasnikov, N. (Research Co-investigator)
EPSRC (Engineering and Physical Sciences Research Council)
1/12/24 → 1/12/28
Project: Research Studentship Case - Internally allocated
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A multireference excited state database for correlation-aware screening of organic semiconductors in excitonic energy-materials discovery
Zollner, M. & Nematiaram, T., 2 Jun 2026. 1 p.Research output: Contribution to conference › Poster
Open AccessFile2 Downloads (Pure) -
Learning the limits: how data, diversity, and representation control machine-learning predictions of reorganisation energy
Zollner, M., Moshfeghi, Y. & Nematiaram, T., 16 Apr 2026, In: Journal of Materials Chemistry. C . 14, 14, p. 5999-6011 13 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile4 Downloads (Pure)
Datasets
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Data for "Learning the limits: how data, diversity, and representation control machine-learning predictions of reorganisation energy"
Zollner, M. (Creator), Nematiaram, T. (Contributor) & Moshfeghi, Y. (Contributor), University of Strathclyde, 12 Feb 2026
DOI: 10.15129/fbb78cbc-64e5-4c24-983a-d258a1e92367
Dataset
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Data for: "Organic materials repurposing, a data set for theoretical predictions of new applications for existing compounds"
Nematiaram, T. (Contributor) & Omar, Ö. H. (Creator), University of Liverpool, 6 Feb 2023
DOI: 10.17638/datacat.liverpool.ac.uk/1472
Dataset
Prizes
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Best Poster Prize - The Leverhulme Research Centre for Functional Materials Design Symposium
Nematiaram, T. (Recipient), 2022
Prize: National/international honour
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Activities
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Next Generation of AI Chemists | Imperial College London
Nematiaram, T. (Speaker)
7 Jul 2026Activity: Talk or Presentation › Invited talk
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A Multireference Excited State Database for Correlation-Aware Screening of Organic Semiconductors in Excitonic Energy-Materials Discovery
Zollner, M. (Speaker) & Nematiaram, T. (Contributor)
16 Jun 2026Activity: Talk or Presentation › Oral presentation