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PhD position in Single Particle Analysis and CLEM Correlative Imaging.

Description: We are looking for a candidate with a PhD in Computer Science, Mathematics, Engineering, Physics or equivalent with software development skills, preferrably applied to Structural Biology, Biomedical Imaging, or Imaging in general.

The candidate will work on the development of image processing algorithms for Single Particle Analysis (especially, continuous heterogeneity analysis) and CLEM Correlative imaging (especially, image alignment and segmentation). The contract is for 4 years and will be developed along with Dr. Eva Nogales (from Univ. Calif. Berkeley) in the context of the JAE-CHAIR grant “ALLCRYO. Technical developments for the improvement of the cryoEM workflow, and their application for the structural characterisation of conformationally and compositionally heterogeneous samples in vitro and in vivo.

Location: Madrid

Required Skills:

  • PhD in Computer Science, Mathematics, Engineering, Physics or equivalent
  • Programming experience with Python
  • Experience in Linux
  • Experience in Structural Biology, Biomedical Imaging, General Imaging or Bioinformatics

Interested candidates should send their CV’s and letter of interest to i2pc@cnb.csic.es

PhD position in fluorescence microscopy image processing.

The Biocomputing Unit of the National Biotechnology Centre is looking for excellent master students in Engineering, Physics, Mathematics or any other field related to data analysis. The PhD would be in fluorescence microscopy image processing.

This project involves several fast-growing technologies: electron cryo-microscopy and deep learning. Our laboratory is located at the Centro Nacional de Biotecnología in Madrid, a reference institute in Spain in cryo-EM, with highly advanced fluorescence microscopy facilities. Moreover, our group is a world reference in this field. In this work we intend to follow two main lines of work:

  • Spatio-temporal analysis, which will allow a more accurate detection and quantification of dynamic phenomena at the cellular level, thus facilitating the exploration of complex biological processes in real time
  • Correlative microscopy: To implement and refine correlative microscopy techniques to efficiently integrate data obtained through different fluorescence microscopy modalities, as well as scanning electron microscopy (SEM) and transmission electron microscopy (TEM).

Latest publications

  1. Cayuela, P. Conesa, A. Oña, J.A. Gómez-Pedrero, C.O.S. Sorzano. Real-Time Correction of Chromatic Aberration in Optical Fluorescence Microscopy. Methods and Applications in Fluorescence, 11: 045001 (2023)
  2. Cayuela-López, J.A. Gómez-Pedrero, A.M. Oña Blanco, C.O.S. Sorzano. Cell-TypeAnalyzer: A flexible Fiji/ImageJ plugin to classify cells according to user-defined criteria. Biological Imaging, 2: e5 (2022)
  3. Cayuela, E. García-Cuesta, J.A. Gomez-Pedrero, S.R. Gardeta, J.M. Rodriguez-Frade, M. Mellado, C.O.S. Sorzano. TrackAnalyzer: A Toolbox for a holistic analysis of Single-Particle Tracks. Biological Imaging, 3: e18 (2023)

Interested candidates should send their CV’s and letter of interest to: blanca@cnb.csic.es or coss@cnb.csic.es

Artificial intelligence for macromolecular analysis and pharmaceutical ligands design

What we are looking for : We are looking for PhDs in engineering, physics, mathematics, computing science or any related scientific domain with a strong will to apply the AI methods to Structural Biology and Drug Screening. Knowledge of Python and Deep learning libraries are a must. Previous knowledge of Bioinformatics or Biology is highly appreciated, although not compulsory. The Postdoc must propose a research proposal aligned to the presented challenge.

The context : Structural biology is key to understanding biological macromolecules like proteins and nucleic acids, crucial for biological functions and diseases. Cryo-electron microscopy (cryoEM) revolutionizes this field by visualizing macromolecules at near-atomic resolution, facilitating their study in native states. Simultaneously, computational prediction of ligand binding is vital for drug discovery, helping identify therapeutic candidates by how they interact with biomolecules. The synergy of AI tools for cryoEM and ligand prediction accelerates understanding biological systems and developing new treatments.

 

The problem to address : The journey from pixelated snapshots to precise atomic models is fraught with computational hurdles, requiring a blend of innovative AI techniques and a deep understanding of molecular landscapes. Parallel to this endeavor is the quest to discover ligands that snugly fit into these newly revealed structures, a critical step in the design of new drugs. This challenge involves sifting through vast chemical libraries to find those rare molecules that can bind with high affinity to target sites on the macromolecule.

 

Objectives:

  • Elucidating the complex structures of biological macromolecules from CryoEM images.
  • Discover ligands that fit into the structures revealed for new drug design.

 

Expected Outcomes: Robust algorithms and workflows to tackle both problems.

New position open: Software Developer in the Biocomputing Unit (BCU), Instruct Image Processing Center (I2PC), Madrid

Description: We are looking for a candidate with a BSc/MSc in Computer Science, Mathematics, Engineering, Physics or equivalent with software development skills. The candidate will be involved in European and National projects related to cloud and open data technologies, being part of a team in charge of developing data management software for Instruct facilities.

Thus, the candidate will participate in projects that will shape and influence strategies for making research data generated across the Instruct-ERIC infrastructure FAIR (Findable, Accessible, Interoperable, Reusable). This data transformation will involve considerations of the storage, metadata description and deposition of large datasets for use and reuse including artificial intelligence. These data will come primarily from structural biology but can include data from other diverse research domains.

Background: INSTRUCT ERIC is the European Strategic Initiative in the area of Integrative Structural Biology. It is organized as a distributed infrastructure with “Instruct Centers” and the BCU hosts the “INSTRUCT Image Processing Center (I2PC)”.

 BCU is well known in the area of 3D-EM, with over 200 publications in the area of Electron Microscopy and large contributions to open source scientific software, like Scipion, Xmipp and 3DBionotes.

For further information go to INSTRUCT Image Processing Center or  Biocomp web sites.

Location: Madrid 

Required Skills:

  • BSc / MSc in Computer Science, Mathematics, Engineering, Physics or equivalent
  • Programming experience with Python
  • Experience in Linux
  • Medium level of proficiency in written and spoken English

The following skills are considered a “plus”, but are not essential:

  • Experience of the full lifecycle of software architecture, design, and implementation
  • Experience developing web and desktop Python apps
  • Knowledge and some degree of experience using relational and/or noSQL databases.
  • Experience in assisting open source software development teams (GitHub, documentation, user support, collaboration tools…).
  • Interest or experience in scientific data management
  • Interest or experience in biological sciences or bioinformatics
  • Experience in Virtualization: Docker

nterested candidates should send their CV’s and letter of interest to i2pc@cnb.csic.es