Bioinformatics and Computational Protein Design Engineer (M/F)

Job Description

Missions

The 'Study and Design of Biologically Active Compounds' group, within the Laboratory of Tissue Biology and Therapeutic Engineering, is recruiting a Bioinformatics and Computational Protein Design Engineer.
The aim of the project is to develop a robust, reproducible and automated computational pipeline for the computational design of proteins and peptides, drawing on the latest methods in artificial intelligence and structural modelling.
The successful candidate will be primarily responsible for the design and development of the pipeline, the integration of various computational protein design tools, and the implementation of procedures to automatically test and evaluate the generated designs.
The project will be carried out within an interdisciplinary environment combining bioinformatics, structural biology, biophysics and experimental biology.
The candidate will be supervised on the scientific and methodological aspects of computational protein design by a researcher who is an expert in the field. Prior knowledge of all computational protein design methods is therefore not required.
The primary aim is to recruit an engineer with strong skills in scientific programming and bioinformatics, capable of mastering new methods and integrating them into reproducible workflows.

Activity

Development of a computational protein design pipeline

The candidate will develop a workflow to automate various design stages:
Structure generation → Sequence design → Structural prediction → Analysis → Filtering and ranking

The pipeline may notably incorporate:
• RFdiffusion for structure generation;
• ProteinMPNN for sequence design;
• AlphaFold for structural prediction and evaluation;
• RoseTTAFold for structural prediction and comparison;
• Rosetta for the analysis and scoring of designs.
The aim will be to develop an architecture that allows for the easy integration of different tools and methods, and to adapt the workflow as the project progresses. Prior knowledge of these tools is an advantage.

Pipeline engineering and automation

The candidate will be responsible for the IT implementation of the workflow.
Their duties will include, in particular:
• developing Python scripts and modules;
• automating scientific workflows;
• integrating existing software and computational models;
• managing input and output formats;
• managing parameters and configurations;
• automation of computational campaigns;
• execution and management of calculations on GPUs/HPC;
• implementation of monitoring and logging systems;
• error handling and calculation retries;
• use of Git and implementation of best practice development procedures;
• documentation of code and workflows;
• implementing procedures to ensure the reproducibility of calculations.

Development of a testing and validation strategy
The pipeline will be tested on various test cases to verify its functionality and evaluate the performance of the different methods.
This stage will ensure that a workflow validated against test cases is in place before it is applied to a new biological problem.

Application to peptide design
In a second phase, the developed pipeline will be applied to a computational peptide design project.

Your Profil

Skills

The candidate must hold a bachelor's degree in one of the following fields; a master's degree in the same fields would be an asset:
• bioinformatics;
• computational biology;
• structural bioinformatics;
• computer science applied to the life sciences;
• artificial intelligence / machine learning applied to biology;

Essential skills
Very good command of Python;
• experience in scientific programming or workflow development;
• good knowledge of the Linux environment;
• Ability to use and integrate scientific software;
• knowledge of Git and the principles of software development;
• ability to analyse and manipulate biological or structural data;
• the ability to work independently in finding technical solutions;
• strong analytical and problem-solving skills.
• Desirable skills

Experience in one or more of the following areas would be an advantage:
• structural bioinformatics;
• molecular modelling;
• protein structure prediction;
• protein design or peptide design;
• machine learning / deep learning;
• scientific computing on GPUs;
• HPC environment;
• development of bioinformatics pipelines.

Experience with RFdiffusion, ProteinMPNN, AlphaFold, RoseTTAFold or Rosetta would be an advantage but is not essential.
Prior knowledge of all these tools is not expected. Above all, we are looking for a candidate with strong technical skills and the ability to learn new methods quickly.

Desired skills
Scientific and technical curiosity;
• Independence and rigour;
• an interest in scientific software development;
• ability to learn new tools quickly;
• ability to work on interdisciplinary problems;
• an interest in data analysis and the interpretation of results;
• ability to document one's work;
• good scientific communication skills;
• ability to work collaboratively with researchers and engineers from different disciplines.

Your Work Environment

The ECMo team at the Laboratory of Tissue Biology and Therapeutic Engineering – UMR 5305 CNRS / UCBL specialises in the molecular modelling of small molecules, peptides and proteins in complex environments. The team consists of five permanent members. The successful candidate will receive direct scientific supervision on computational protein design and structural modelling approaches.

This supervision will enable the candidate to gradually develop their skills in protein and peptide design methods, in particular:
• structure generation using RFdiffusion;
• sequence design using ProteinMPNN;
• structural prediction using AlphaFold and RoseTTAFold;
• analysis and scoring using Rosetta;
• strategies for selecting and ranking designs.

where applicable, a description of any IT or scientific projects completed.
Applications from candidates with different educational backgrounds but with relevant experience in scientific programming, bioinformatics or machine learning applied to the life sciences will be given careful consideration. Prior knowledge of computational protein design tools is not essential.

Constraints and risks

No biological or chemical risks

Compensation and benefits

Compensation

from €2,521 gross per month, depending on experience

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

The research professions