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Sustaining innovation postdoctoral research associate – deep learning methods for rapid cryo-em[...]

Cambridge
Astex Pharmaceuticals
Research associate
€37,500 a year
Posted: 21h ago
Offer description

Organisation/Company Astex Pharmaceuticals Research Field Biological sciences Computer science Medical sciences Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Application Deadline 31 May 2026 - 00:00 (Europe/London) Country United Kingdom Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No


Offer Description

Job Description

Astex Pharmaceuticals and IE University are offering an exciting joint postdoctoral opportunity focused on the development of next-generation deep learning algorithms for cryo-electron microscopy (cryo-EM) single particle analysis (SPA).

The successful candidate will work at the intersection of artificial intelligence, computer vision, structural biology, and computational imaging, contributing to cutting‑edge research in 3D pose estimation under extremely low signal‑to‑noise conditions. The project combines large‑scale cryo‑EM datasets with modern deep learning and representation learning approaches.

The position is ideal for researchers with strong expertise in machine learning, computer vision, computational imaging, or scientific computing who are interested in applying advanced AI methodologies to challenging real‑world biological problems. Prior cryo‑EM experience is welcome but not mandatory.

The researcher will collaborate closely with both industrial and academic teams, benefiting from:

* Access to Astex’s state‑of‑the‑art cryo‑EM facility and large‑scale data infrastructure
* Expertise from leading cryo‑EM and AI researchers
* Opportunities for high-impact publications and open‑source software development
* Exposure to translational drug discovery applications

This is a 3-year fixed‑term position based primarily in Cambridge, UK, with regular collaboration visits to Madrid, Spain.

Research Project Description

The project focuses on advancing deep learning methods for rapid and robust cryo‑EM pose estimation in single particle analysis workflows.

The research will build upon recently published cryoPARES methodologies and explore foundation‑model and representation‑learning strategies for cryo‑EM data analysis using petabyte‑scale datasets. The overall objective is to improve the inference of 3D particle poses from low signal‑to‑noise ratio cryo‑EM images and enhance traditional reconstruction pipelines through AI‑driven approaches.

The project leverages:

* Large‑scale cryo‑EM datasets generated at Astex Pharmaceuticals
* Existing open‑source tools developed by Prof. Ruben Sanchez‑Garcia’s group
* Modern deep learning frameworks and scalable computational infrastructure
* Interdisciplinary collaboration between academia and industry

The work has direct applications in structural biology and AI‑enabled drug discovery.

Main Responsibilities

* Develop novel deep learning algorithms for cryo‑EM single particle analysis
* Advance AI‑based 3D pose estimation methods for low‑SNR imaging data
* Design and train representation learning and foundation models for cryo‑EM applications
* Publish research findings in leading peer‑reviewed journals and conferences
* Contribute to open‑source software development for the scientific community
* Collaborate with interdisciplinary teams across academia and industry
* Participate in scientific meetings, technical discussions, and collaborative research activities
* Contribute to maintaining high scientific and technical standards throughout the project


Where to apply

E-mail recruitment.uk@astx.com


Requirements

Research Field Computer science » Other Education Level PhD or equivalent

Skills/Qualifications

* PhD in:
o Computer Science
o Mathematics
o Computational Science
o Artificial Intelligence
o Physics
o Engineering
o Or another relevant quantitative/computational discipline
* Alternatively, equivalent research experience in a relevant area

Candidates must demonstrate at least one of the following:

* Strong expertise in cryo‑EM SPA image processing and algorithm development
* Strong experience in computer vision or deep learning using frameworks such as PyTorch, JAX, or TensorFlow, with interest in cryo‑EM applications

Specific Requirements

* Excellent programming skills in Python
* Familiarity with Git version control
* Knowledge of C/C++ is desirable
* Strong understanding of deep learning and/or computer vision methods
* Experience with machine learning frameworks (PyTorch, JAX, TensorFlow)
* Excellent analytical and problem‑solving abilities
* Strong communication and teamwork skills
* Ability to work in interdisciplinary and international environments
* Scientific writing and publication experience
* Highly competitive salary and benefits package
* Hybrid and flexible working options
* Access to state‑of‑the‑art cryo‑EM infrastructure
* Collaboration with internationally recognised researchers and industry experts
* Excellent training and career development opportunities
* Participation in high‑impact interdisciplinary research
* Opportunity to contribute to AI‑driven drug discovery initiatives
* International and inclusive research environment

Eligibility criteria

* Candidates must already hold the right to work in Spain or be EU nationals
* Successful candidates will be subject to right‑to‑work verification procedures
* Willingness to travel regularly between Cambridge (UK) and Madrid (Spain)

Selection process

* Initial screening of applications
* Evaluation of scientific background and technical expertise
* Assessment of alignment with the project objectives
* Interviews with representatives from Astex Pharmaceuticals and IE University
* Final candidate selection based on scientific excellence, technical skills, and collaborative potential

Additional comments

Applicants should submit their application(including CV + Cover Letter) by email to:

The subject line must clearly include the reference:

SIPD/0426

Applications must be submitted before midnight on 31 May 2026.

#J-18808-Ljbffr

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