Postdoc position in computational protein design at the Bioinformatics group at BIO@SNS, Pisa

We are looking for an enthusiastic, early-career post-doctoral researcher to join the Bioinformatics group of the Laboratory of Biology (Bio@SNS), Scuola Normale Superiore, Pisa (ITALY). Our main research focus is the understanding of the function of protein systems involved in signal transduction using structural, network and evolutionary bioinformatics as well as machine learning analysis of omics datasets, in both neurodegenerative disorders and cancer. The group is based at the “Area della Ricerca CNR” research campus, embedded in the vibrant research community of Pisa, which includes some of the top Italian universities and research Institutions.

Project Description

The successful candidate should have a strong background in biology and informatics, with a keen interest in biological mechanisms and data analysis. He/she will be involved in a research program aimed at engineering new biologics with theranostic potentials, such as Designer Receptor Exclusively Activated by Designer Drugs (DREADDs) to study specific biologic pathways in vivo and/or antibodies for modulating targets and processes of biomedical relevance in cancer and neurodegenerative disorders. The ideal candidate is expected to apply state-of-art bioinformatics and machine learning techniques for protein design, such as the Rosetta molecular modeling suite, ProteinMPNN, ProtGPT2, as well as implementing customized pipelines through the usage of cutting-edge deep-learning frameworks, such as protein language models and graph neural networks. Previous experience in wet lab molecular biology techniques for protein engineering would be considered a plus. The project will be carried out in close collaboration with Prof. Cattaneo’s group at BIO@SNS.

Key Tasks And Responsibilities
  • Development and application of pipelines to design new biologics in silico;
  • Data analysis (e.g. clustering, PCA) and visual interpretation via molecular graphics of representative candidates, to select the best hits for experimental validation;
  • Collaborating with expert biologists and group members to fine-tune predictions and to optimize validated hits.
  • PhD in a relevant subject area (Computational Biology, Bioinformatics, Biology, Chemistry, Computer Science, Statistics, Mathematics);
  • full working proficiency in a scripting language (e.g. Python, R);
  • knowledge of molecular and structural biology;
  • knowledge of data analysis and machine learning libraries (e.g. pandas, scikit-learn, pytorch, tensorflow, keras);
  • full working proficiency in UNIX/Linux;
  • structural bioinformatics;
  • experience with HPC computing;
  • fluent in English;
  • ability to communicate ideas and results effectively;
  • ability to work independently and to organise own workload;
  • ability to work with others in a collegial manner and to communicate effectively internally at all levels and with selected external individuals;
  • ability to work in a multi-cultural, multi-ethnic environment with sensitivity and respect for diversity.
Following Requirements Will Be Also Favourably Considered
  • Protein interaction network analysis through scripting (igraph, networkx) or Cytoscape;
  • chemoinformatics;
  • full working proficiency in a compiled language (e.g. C, C++, Fortran);
  • ability to deliver effective presentations and scientific talks;
  • ability to devise novel quantitative models;
  • experience in formulating the world in statistical models and applying them to real data;
  • strong publishing record;
How to apply

The position is for two years and is available from spring 2023 or as soon as possible hereafter.

Please apply directly through this link:


For informal inquiries please write to:



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