Lead researcher position in Computational Biology

French National Institute for Health Research (INSERM); France; Sur place; EUR 35 000 - 55 000; Plein temps

Résumé du poste

A leading research institute in France is seeking a skilled computational biologist to innovate therapeutic strategies through advanced computational techniques. The role involves developing models for drug discovery, conducting virtual screenings, and personalizing treatment approaches for rare diseases. Candidates should hold a PhD and possess strong computational and analytical skills in biological contexts.

Qualifications

• PhD in a relevant field; strong background in computational methods and drug discovery.
• Experience with network modeling and in-silico techniques.
• Ability to develop new algorithms for drug repurposing and molecular simulations.

Responsabilités

• Develop computational methods for drug discovery and modeling therapeutic strategies.
• Conduct simulations and screenings to improve drug design and patient treatment personalization.
• Create models to analyze biological interactions and identify therapeutic targets.

Connaissances

Computational Modeling

Drug Design

Biological Network Analysis

Pharmacogenomics

Molecular Target Identification

High-throughput Screening

Formation

PhD in Computational Biology or related field

Description du poste

The successful candidate will develop computational approaches to discover, model, and develop therapeutic strategies. Examples of potential approaches include:

-Network Modeling: Creating computational models to map and analyze interactions within biological networks, thereby identifying key pathways and targets for therapeutic intervention.

-Simulations and Virtual Drug Screenings: Aiding in drug design by modeling and assessing modifications of biological pathways by targeted interventions.

-In-silico Identification of Molecular Targets: Developing novel computational techniques to identify molecular targets critical for developing new therapies for rare diseases, based on genetic data and biological system simulations.

-Computational Drug Repurposing: Developing novel algorithms and databases to identify existing drugs that may be repurposed for rare disease treatments, accelerating the development process by leveraging known drug safety profiles.

-Structural Biology: Implementing computational structural biology methods, such as molecular modeling and simulations, to understand the 3D structures of proteins and their interactions with potential drugs.

-High-throughput In-silico Drug Screening: Conducting extensive in-silico screenings using virtual libraries of compounds to efficiently predict interactions with target proteins and select promising therapeutic candidates.

-Treatment Eligibility: Implementing computational methods and pharmacogenomics strategies to determine which patients with rare diseases are likely to benefit from specific therapies, ensuring personalized and effective treatment.