The Institute 
 
The Centre for Genomic Regulation (CRG) is an international biomedical research institute of excellence, based in Barcelona, Spain, with more than 400 scientists from 44 countries. The CRG is composed by an interdisciplinary, motivated and creative scientific team which is supported both by a flexible and efficient administration and by high-end and innovative technologies. 


In April 2021, the Centre for Genomic Regulation (CRG) received the renewal of the 'HR Excellence in Research' (https://www.crg.eu/en/content/careers/hr-excellence-research) Award from the European Commission. This is a recognition of the Institute's commitment to developing an HR Strategy for Researchers, designed to bring the practices and procedures in line with the principles of the European Charter for Researchers ( https://euraxess.ec.europa.eu/jobs/charter/european-charter) and the Code of Conduct for the Recruitment of Researchers (Charter and Code) ( https://euraxess.ec.europa.eu/jobs/charter/code).

Please, check out our Recruitment Policy:

https://www.crg.eu/sites/default/files/crg/crg_recruitment_policy.pdf


The role  
 
The AI for protein design group at the CRG is inviting applications for a role centered at the intersection between protein AI models and gene editing. Our goal is to design novel protein-based gene writers with improved efficacy and safety. The candidate will train large language and diffusion models to provide new protein variants that will be tested in the laboratory. 
 
The main responsibilities will include implementing and using machine learning models for the design of gene writer sequences. 
 
About the team  
 
This research group is focused on using computational and experimental approaches to understand and design protein functions. We have extensive experience in deep unsupervised learning and protein design, which we have applied to various projects (see https://www.aiproteindesign.com). 
Over the next few years, we will expand our focus to include the design of custom-tailored and new-to-nature protein functions. We will implement models, understand their decision-making process using XAI and improve their performance through reinforcement learning. We will also include experimental characterization efforts, allowing continual improvement of our models. We train new models for protein engineering and design and test the experimentally at our facilities. Explore our lab’s work at www.aiproteindesign.com. 
 
Whom would we like to hire?  
Professional experience 
 
Must Have 
We seek exceptional candidates with a passion for computation and deep learning to solve biomedical challenges. 
Experience in bioinformatics, computational structural biology, or computational biology. 
Good understanding of software engineering and good code practices. 
The capability of working independently on very fast-paced science. 
 
Desirable but not required/ Nice to have 
PhD in Bioinformatics, Synthetic Biology or a related field.  
Experience in protein or enzyme design. 
Knowledge about gene editing technologies such as CRISPR‐associated nuclease‐based tools.  
 
Education and training 
MSc in Biotechnology Computer Science, Chemistry, Physics, Maths or a related discipline 
 
Languages 
Good communication skills in English 
 
Competences  
Self-motivated, capability of working independently 
 
Technical Skills 
Linux, python programming 
Knowledge computational structural biology (protein visualization and modelling, multiple sequence alignment) 
Knowledge about writing scientific publications (eg. figure preparation) 
Knowledge of data analysis with python (pandas, huggingface, pytorch); handling environments with conda, pyenv; use of scientific clusters (slurm) 
 
The Offer – Working Conditions 
Contract duration: Technical and scientific activities contract linked to the project (estimated 3 years) 
Estimated annual gross salary: salary is commensurate with qualifications and consistent with our pay scales 
Target start date: As soon as possible 
 
We provide a highly stimulating environment with state-of-the-art infrastructures, and unique professional career development opportunities. To check out our training and development portfolio, please visit our website in the training section.( https://www.crg.eu/en/content/training).

We offer and promote a diverse and inclusive environment and welcomes applicants regardless of age, disability, gender, nationality, ethnicity, religion, sexual orientation or gender identity. 


The CRG is committed to reconcile a work and family life of its employees and are offering extended vacation period and the possibility to benefit from flexible working hours. 


Application Procedure 
 
All applications must include: 
A motivation letter addressed to Dr Noelia Ferruz. 
A complete CV including contact details. 
Contact details of two referees. 
 
All applications must be addressed to Dr. Noelia Ferruz and be submitted online on the CRG Career site - http://www.crg.eu/en/content/careers/job-opportunities  
 
 
Selection Process  


Pre-selection: The pre-selection process will be based on qualifications and expertise reflected on the candidates CVS. It will be merit-based.

 
Interview: Preselected candidates will be interviewed by the Hiring Manager of the position and a selection panel if required. 
 
Offer Letter: Once the successful candidate is identified the People department will send a Job Offer, specifying the start day, salary, working conditions, among other important details.  
 
 
Deadline: Please submit your application by October 17th, 2024. 
 
Suggestions: The CRG believes in ongoing improvement and promotes a culture of feedback. This is one of the reasons we have in place, at your disposal as a candidate, a mechanism to gather your suggestions/complaints concerning your candidate experience in our recruitment processes. Your feedback really matters to us in our aim at creating a positive candidate journey. You can make a difference and help us improve by letting us know your suggestions through the following form. https://recruitment.crg.eu/webforms/recruitment-contact-form-suggestionscomplaints
  
CPP2023-010699 financiado por MCIN/AEI/10.13039/501100011033/ FEDER