Connectionists: URGENT: Funded PhD Position in Chemo-Informatics / Deep Learning @ Paris-Saclay

[Jérémie Cabessa]

Offer: Funded PhD Position in Chemo-Informatics / Deep Learning.
Institution: Universities of Versailles and Évry – Paris-Saclay
Application deadline: 22 May 2023 (urgent!)

Dear colleagues,

The laboratories DAVID and LAMBE from the Universities of Versailles and Évry – Paris-Saclay offer a 3-year funded PhD position in the fields of chemo-informatics and deep learning.

The project is entitled Spectral-Based Inverse Molecular Design with Graph Neural Networks and concerns the prediction of graph molecular structures from their vibrational spectra. The application deadline is the 22nd May 2023 (urgent), potentially extendable.

To apply, please send your CV by email to Jérémie Cabessa at: 
jeremie.cabessa at uvsq.fr

The details of the project, working conditions and candidate requirements are provided below.

Thank you and best regards.


Offer: 1 funded PhD position in chemo-informatics and deep learning at the laboratories DAVID and LAMBE from the Universities of Versailles and Évry – Paris-Saclay.

Title and Abstract: Spectral-Based Inverse Material Design with Graph Neural Networks: from vibrational spectra to molecular graphs

In recent years, graph neural networks (GNNs) have significantly progressed theoretically and led to impressive achievements in a large variety of domains, including biology and chemistry. However, graph prediction tasks still represent challenging issues in this domain. In theoretical chemistry, the computational prediction of a molecular structure is a long-standing problem, and vibrational spectroscopy constitutes the major technique for molecular structure identification. The proposed project aims at developing a GNN-based system for the prediction of 2D topological molecular graphs from their vibrational spectral signatures. In machine learning, this projects fits into the direction of graph prediction and inverse problems in general. In theoretical chemistry, it aims to contribute to the impactful research on inverse molecular/material design.

Candidate requirements: Strong background in ML and neural networks; very good programming skills, preferably in Python; experience with neural network libraries like PyTorch or Keras is strongly recommended; prior knowledge in theoretical chemistry is a plus.

Funding information: 3 year scholarship from the Graduate School ISN and Convergence Institute DATAIA, in accordance with the French standards regarding PhD salaries.

Deadline (urgent!): 22 May 2023, potentially extendable.

Application details: Please send your CV by email to Jérémie Cabessa at 
jeremie.cabessa at uvsq.fr

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