Phd Position For Artificial Intelligence And Computer Vision In Cryo Electron Tomography

CSIC; País Vasco; Presencial; EUR 24.000; Jornada completa

Descripción de la vacante

A leading research institute in Spain seeks a predoctoral PhD candidate for a position focused on Artificial Intelligence and Computer Vision in Cryo Electron Tomography. The role involves developing new methodologies, software maintenance, and analyzing datasets. Candidates should have a degree in relevant fields and experience in deep learning. The position offers a 4-year contract with a salary of €24,000 gross per year and ample benefits.

Servicios

Ample fiscal benefits

Formación

• Ideal candidates hold an official degree in Mathematics, Computer Science, Engineering or similar.
• Experience in Deep Learning or other AI methods.
• Good command of MATLAB, Python, C++ and/or CUDA.

Responsabilidades

• Contribute to the development of new methodologies integrating deep learning techniques with Dynamo.
• Assist in the ongoing development and maintenance of the software platform and related tools.
• Analyze cryoET datasets provided by external collaborators.

Conocimientos

Strong background in Matlab

Experience in Deep Learning

Proficiency in MATLAB, Python, C++ and/or CUDA

Solid background in numerical mathematics

Strong interest in Life Sciences

Educación

Official degree in Mathematics, Computer Science, Engineering or similar

Descripción del empleo

Overview

The Instituto Biofisika (CSIC-UPV/EHU) located at the Leioa Campus of the University of the Basque Country will open a call for a predoctoral PhD position in Artificial Intelligence and Computer Vision in Cryo Electron Tomography. The successful candidates will join the Laboratory for Numerical Methods of Cryo Electron Tomography (cryoET), led by Dr. Daniel Castaño Díez. The group develops computational methodologies for automated analysis and interpretation of 3D cellular imagery, primarily through its in-house software platform Dynamo. We offer a PhD contract linked to the project PID***********NB-I00, “Graph Learning for Classification and Segmentation in Cryo‑Electron Tomography,” funded by the Spanish Ministry of Science, Innovation and Universities. The project aims to extend Dynamo with novel deep learning techniques for identifying and characterizing small, flexible proteins within their natural surroundings. The successful applicant will contribute to developing these methodologies, as well as to ongoing software development and maintenance, and will analyze cryoET datasets provided by external collaborators. This is a full‑time, 4‑year position funded by the Spanish Ministry of Science, Innovation and Universities (PID***********NB-I00) with support from MICIU/AEI/FEDER, UE and by the FSE+.

Responsibilities

• Contribute to the development of new methodologies integrating deep learning techniques with Dynamo.
• Assist in the ongoing development and maintenance of the software platform and related tools.
• Analyze cryoET datasets provided by external collaborators.

Qualifications

• Ideal candidates hold an official degree in Mathematics, Computer Science, Engineering or similar, with a strong background in Matlab.
• Strong interest in Life Sciences research.
• Experience in Deep Learning or other AI methods.
• Solid background in numerical mathematics, including optimization and heuristic optimization methods.
• Proficiency in software prototyping and production; good command of MATLAB, Python, C++ and/or CUDA.

Additional qualifications

• Experience in Image Processing for Electron Microscopy.
• Experience in Image Processing for Light Microscopy.
• Experience in Molecular Dynamics Simulations.

Contract and Start

The position has a flexible incorporation date with an expected start in Winter/Spring **** and is secured for a 4‑year period.

Salary

Salary is fixed at around €24,000 gross per year for a BSc/MSc holder, with ample fiscal benefits.

Application Information

Expressions of interest should be directed to ****** in a single PDF and include: Curriculum Vitae with academic record, Two reference letters or contact email of referees.