Senior Scientist – Integrated in Silico Antibody Engineering (m/f/d)

image]**Senior Scientist – Integrated in Silico Antibody Engineering (m/f/d)****Servier Symphogen is inspired by nature, led by science, and driven by people.**Servier Symphogen is the Antibody Center of Excellence within the Servier Group. We combine computational methods, antibody engineering, and experimental workflows to support the discovery and development of differentiated therapeutic antibodies.We are looking for a Senior Scientist to join the Computational Antibody Design team within the Antibody Technology department.This position focuses on the development and integration of machine learning methods supporting antibody engineering, candidate optimization, and experimental decision-making workflows. You will work at the interface between computational and experimental research, contributing to DMTA/DMTL cycles, active learning strategies, and data-driven antibody optimization approaches.**Key responsibilities**Conduct innovative research in antibody discovery with a focus on integrated machine learning approaches for antibody engineeringDevelop and implement computational models for antibody property and function prediction supporting antibody optimization and candidate selectionIntegrate computational methods into experimental workflows and therapeutic project decision-making processesContribute to the development of computational approaches supporting DMTA/DMTL cycles for antibody property, format, and function optimizationDevelop methods for optimal experimental design, including Bayesian approaches and information-driven strategiesSupport the implementation of active learning approaches within antibody discovery workflowsCollaborate with cross-functional teams to integrate computational findings into therapeutic programs and platform development activitiesWork closely with experimental scientists, technicians, bioinformaticians, data scientists, and ML engineers across research programsEstablish and contribute to collaborations with academic and industry partners**Required Qualifications**Ph.D. in Bioinformatics, Computational Biology, Data Science, Computational Chemistry, Biophysics, Computer Science, or a related fieldExperience in computational drug discovery or related interdisciplinary research environmentsExperience with protein property prediction and optimization modelsStrong understanding of machine learning and statistical methods, including Bayesian approachesStrong interest in experimental antibody discovery workflows and experience collaborating with wet-lab scientistsExperience with active learning, information-driven optimization approaches, or DMTA workflows is considered advantageousStrong Python programming skills and familiarity with version control systemsAbility to communicate scientific concepts effectively in a multidisciplinary research environmentCollaborative, rigorous, and scientifically curious working style** ****What Servier Symphogen offers**An integrated computational and experimental antibody research environmentClose collaboration across scientific disciplines and international research teams within Servier Symphogen and Servier GroupOpportunities to contribute directly to therapeutic antibody discovery and platform developmentThis position is offered as a 3-year temporary contractProfessional development opportunities within an international research organizationFlexible working conditions and competitive compensation**Application **The recruitment is outsourced to external Recruiter Aims International Denmark.**To apply for this job, email your details to **Ferhan Cetinkaya – [f.cetinkaya@aims-germany.com | aimsinternational.com quoting project number “DK-0025p”AIMS International-Denmark ApS World Trade Center Ballerup#MachineLearning #ComputationalBiology #AntibodyEngineering #DrugDiscovery #BiotechJobs