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PhotoCaM: Photosynthetic Antennas in a Computational Microscope

Training a new generation of computational scientists

A Marie Skłodowska-Curie Actions Doctoral Network funded by the European Union
Starting date: January 2024


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Photosynthesis relies on harvesting the sun light and on transforming the solar energy into chemical energy to sustain almost all life on earth. An enhanced molecular-level understanding of photosynthesis and particularly of the light-harvesting process is of key significance.

In this Doctoral Network we aim at training a new generation of computational scientists which can treat complex and interdisciplinary problems such as light harvesting on a molecular level using theoretical and computational tools. The interdisciplinary nature of the problem requires a combined knowledge from biology, chemistry, physics and computer science in order to combine state-of-the-art approaches like molecular dynamics simulations, quantum chemistry, theoretical spectroscopy and machine learning into multi-scale schemes.

This joint undertaking is a unique chance in research but especially also in training young scientists in interdisciplinary teamwork, method training and high-performance computing in academic as well as non-academic settings.

Network Partners


Associated partners

Individual research projects

The scientific approach employed in this Doctoral Network has the advantage of combining diverse aspects of computational modelling to pursue the scientific objectives of the project. While the light-harvesting complexes are large biological systems, the excited state calculations determine detailed quantum chemical knowledge. The propagation of the excitation energy and the determination of non-linear spectra are more based on the area of (bio)physics. Most of the computations are numerical expensive and together with machine learning techniques, the development, adaptation and optimization of the involved numerical codes belongs to the area of computer science.

The employed methods exert strong complementarity in a way that at the end the Doctoral Candidates will gain expertise in individual methodologies but also acquire the necessary insight into a holistic view of computational modelling, a crucial characteristic of a new generation of computational scientists in biological and biophysical applications. Molecular dynamics simulations (Projects 2, 6, 10) will give input to the quantum structure and (exciton) dynamics methodologies (Projects 1, 3, 8, 9) with the latter being necessary for the spectroscopic description of light-harvesting complexes (Projects 4, 5, 7). Despite the complementarity of the employed methodologies, the individual projects can stand also independently of each other to a large degree though they evolve their full power only in combination.

  • Project 1: Exciton transfer and NPQ in diatoms: A multi-scale approach employing machine learning (Kleinekathöfer, Bremen, Germany)
  • Project 2: The Configurational Space of Fucoxanthin and Chlorophyll-a/c binding proteins (FCP) in diatoms (Daskalakis, Patras, Greece)
  • Project 3: Multiscale modeling of energy transport for light-harvesting and non-photochemical quenching in higher plants (Mennucci, Pisa, Italy)
  • Project 4: Spectroscopic Signatures of Exciton Annihilation and Quenching (Jansen, Groningen, Netherlands)
  • Project 5: Development of simulation approaches for nonlinear spectroscopy of molecular complexes (Abramavicius, Vilnius, Lithuania)
  • Project 6: The configurational space of LH complexes from higher plants – sensing and response to pH changes (Liguori, Castelldefels, Spain)
  • Project 7: Charge transfer states and higher excited states in light-harvesting (Renger, Linz, Austria)
  • Project 8: Non-adiabatic dynamics in LH complexes with the use of Machine Learning algorithms (Elstner, Karlsruhe, Germany)
  • Project 9: Environmental effects (solvent and protein chain) on high accuracy QM excited-state calculations via multiscale QM/MM on the light harvesting complex (Faccts, Cologne, Germany)
  • Project 10: pKa prediction for LHC residues, in the presence of LHC-protein and LHC-carotenoid, lipid interactions (OneAngstrom, Grenoble, France)


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How to apply for the PhD Positions?

10 fully EU-funded PhD positions available!

  • The PhD candidate should hold an M.Sc. in (Bio)Physics, Chemistry, (Molecular) Biology, or related disciplines.
  • Willingness to work on highly interdisciplinary theoretical/computational projects.
  • Proficiency in programming, e.g., in Python will certainly be an advantage.
  • Depending on the actual selected project, previous hands-on experience in running molecular dynamics or quantum chemistry codes will be highly appreciated.
  • Good English skills.

The EU provides support for each recruited researcher in the form of

  • Competitive monthly salary, indexed to the cost of living in the country where the Doctoral Candidates will be hosted. Details can be discussed during the application process.
  • Mobility allowances.
  • If applicable, family, long-term leave, and special needs allowances.

Supported researchers must be doctoral candidates, i.e., not already in possession of a doctoral degree at the date of the recruitment. Candidates should comply with the mobility rules: in general, they must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting organization for more than 12 months in the 36 months immediately before their recruitment date. Candidates can be of any nationality.

All applications proceed first through the online process. Candidates should apply electronically with their CV, cover letter and transcripts as a single file. Shortlisted candidates may be invited for online interviews and, if selected, may need to make a separate application to the university awarding the PhD degree, according to the requirements of that university.

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Please fill the form and send Cover Letter, CV, MSc&BSc diploma incl.
Grade Transcripts by email as one pdf file (10 MB max.) to

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Project details

Funded by the European Union through
Program: Marie Skłodowska-Curie Actions within Horizon Europe (HORIZON)
Topic: Doctoral Networks (MSCA-DN)
Starting date: January 1, 2024
Duration: 4 years
Grant agreement ID: 101119442
Budget: € 2 589 847,20
EU Fact Sheet:

This project has received funding from the European Union’s Horizon Europe Research and Innovation Program under the Marie Skłodowska-Curie grant agreement No 101119442.