Senior Computational Chemist

**About AQEMIA** AQEMIA is a next-gen pharmatech company generating one of the world's fastest-growing drug discovery pipeline. We already delivered several drug discovery successes within our internal pipeline and through collaborations with pharmaceutical companies. Our most advanced programs are currently in vivo optimization. **About the team you’ll join** You will be an essential part of a dynamic team, contributing to internal Drug Discovery initiatives and collaborative projects with external partners. Each Drug Discovery program team typically consists of a Program Lead, one Senior Medicinal Chemist, two Drug Hunters (each dedicating 50% of their time), and support from a Biologist as needed. Our team structure is flexible, frequently evolving to adapt to the specific needs and stages of our programs, ensuring that we leverage the right expertise at the right time to drive our innovative efforts forward. You'll work closely with talented colleagues of diverse backgrounds and expertise including but not limited to machine learning engineers, project managers, medicinal chemists and physicists. **Your role as a Senior Drug Hunter at Aqemia**: - ** Molecule Design**: You will design and generate small molecules targeting specific therapeutic areas, focusing on affinity and selectivity of validated drug targets, leveraging Aqemia's platform technology. - ** Communication**: Your ability to clearly present and communicate your findings to stakeholders at all levels will be essential. You will ensure that your conclusions are robust and data-driven, fostering trust and collaboration within the team. - ** Feedback and Improvement**: Your project experience and experimental results will provide valuable insights. You will offer systematic feedback on Aqemia's platform, driving continuous improvement and enhancing our technological capabilities. - ** Innovation and Advocacy**: You will proactively propose and implement new approaches to advance our Drug Discovery programs. Your innovative mindset will help improve Aqemia's technology for greater accuracy, speed, and scalability, keeping us at the forefront of scientific discovery. - ** Interdisciplinary Collaboration**: Your collaboration with machine learning engineers, project managers, medicinal chemists, and physicists will be pivotal in pushing the boundaries of what is possible in drug discovery. **Expected Milestones**: - ** First Month**: Familiarize yourself with Aqemia’s processes and pipelines, and provide feedback through a “discovery report". - ** Within Three Months**: Operate independently on drug discovery programs and present project outcomes to stakeholders. - ** Within Six Months**: Mentor new team members, contribute to technology development, and advance drug discovery programs to the lead optimization phase. **Expertise we are looking for**: - ** Industry Experience**: At least 3 years of experience in pharmaceutical, biotech, or CRO companies, with a focus on computational chemistry for small molecule drug discovery. - ** Technical Expertise**: Proficiency in computational chemistry, utilizing structure-based and ligand-based methods. - ** Educational Background**: Ph.D. and/or postdoctoral experience, with a proven track record of technical excellence as evidenced by peer-reviewed publications. - ** Diverse Target Experience**: Experience with various targets, including kinases, GPCRs, phosphatases, ion channels, and bromodomains. - ** Data Proficiency**: Skilled in handling experimental data, including biochemical assays and ADME-Tox data. **Technical skills**: - ** Proficiency in Python in Linux/UNIX environments.**: - Familiarity with **standard computational chemistry packages** (e.g., RDKIT, OpenMM, Ambertools, GROMACs, parmed, Open Babel). - Extensive knowledge of **protein structures and interactions**. - Experience in **structure-based drug design and chemoinformatics techniques**such as: Protein homology, modeling Small molecule docking and pharmacophore hypothesis generation, Virtual (in silico) screening, Structure-activity relationship (SAR) analysisQSAR and ADMEt property modeling, Multi-property optimization-based compound design, Free energy based affinity prediction, Molecular dynamics simulations - Broad understanding of **medicinal chemistry principles and computational methods** for optimizing drug properties. - Ability to **analyze chemical data and identify trends using statistical methods** to ensure reproducibility and data-driven decision-making. **Our recruitment process**: - ** 1** Hiring manager interview: you'll meet your future manager (1h, visio call) - ** 2**Technical assessment of your skills: questions on molecular modeling, medicinal chemistry, molecular docking and cheminformatics, with an expert from the team (1h, visio call) - ** 3**Culture-fit interview with our co-founder and COO Emmanuelle (45min, visio call) - ** 4**Final interview with our co-founder and CEO Maximilien (45min,