Overview A global biopharmaceutical company on a mission to Solve On Incyte follows science to find solutions for patients with unmet medical needs. Through the discovery development and commercialization of proprietary therapeutics Incyte has established a portfolio of first-in-class medicines for patients and a strong pipeline of products in Hematology Oncology and Inflammation and Autoimmunity Headquartered in Wilmington Delaware Incyte has operations in North America Europe and Asia. We are seeking a highly motivated Computational Chemist to join our drug discovery team focusing on computer-aided drug discovery CADD. The successful candidate will apply advanced computational approachesincluding molecular docking free energy perturbation FEP molecular dynamics MD AIML methods and both structure-based and ligand-based drug designto drive small molecule discovery across multiple therapeutic areas. This role will work at the interface of computational and experimental sciences partnering closely with medicinal chemists structural biologists and data scientists to accelerate target validation hit identification lead optimization and candidate selection. The candidate is expected to generate hypotheses influence design decisions and contribute to advancing programs toward clinical development. Essential Functions of the Job Key responsibilities Lead and execute computational modeling initiatives for multiple internal drug discovery programs guiding decision-making from target validation through hit identification and lead optimization Apply and integrate computational chemistry methodologiesincluding molecular docking virtual screening pharmacophore modeling molecular dynamics MD quantum mechanics QM methods and free energy calculations FEPTIto generate mechanistic insights and guide SAR Drive compound design by integrating structure-based SBDD and ligand-based LBDD approaches contributing actionable insights to medicinal chemistry and advancing design cycles Develop and apply AIML models for molecular property prediction compound prioritization and de novo design Collaborate cross-functionally to interpret experimental data biochemical biophysical structural and refine hypotheses to support decision-making Build maintain and improve computational workflows and pipelines emphasizing automation scalability and reproducibility Evaluate and implement emerging computational technologies and methodologies to enhance discovery capabilities Communicate scientific findings and recommendations through presentations reports and publications Support and manage external collaborations e.g. data exchange progress tracking and scientific alignment to ensure effective partnership and project advancement Qualifications Minimal acceptable level of education work experience and competency Ph.D. in Computational Chemistry Chemistry Biophysics Chemical Biology or related field. Postdoctoral experience is preferred particularly in molecular simulation CADD or drug discovery applications Demonstrated experience applying computational methods to small molecule drug discovery with a track record of scientific publications andor impactful program contributions Strong foundation in computer-aided drug discovery CADD methodologies with demonstrated experience applying structure-based SBDD and ligand-based LBDD approaches to drive compound optimization Deep expertise in molecular dynamics MD simulations including system setup execution enhanced sampling techniques custom force field developmentparameterization and advanced trajectory analysis Hands-on experience with core computational chemistry methods molecular docking virtual screening FEPTI industry-standard platforms e.g. Schrödinger CCG MOE and programmingcheminformatics tools Python RDKit Experience working in high-performance computing HPC andor cloud environments with familiarity in workflow automation and reproducible pipeline development e.g. KNIME version-controlled environments Ability to integrate computational predictions with experimental data e.g. crystallography cryo-EM HTS and translate complex datasets into actionable compound design strategies Experience applying AIML approaches e.g. QSAR predictive modeling generative models in drug discovery is strongly preferred Knowledge of ADMEPK and physicochemical property prediction is strongly preferred Key Competencies Strong scientific rigor and critical thinking skills Ability to translate computational insights into practical decisions for drug design Effective communication and collaboration across multidisciplinary teams Ability to manage multiple priorities in a fast-paced matrixed environment High level of initiative curiosity and innovation mindset Disclaimer The above statements are intended to describe the general nature and level of work performed by employees assigned to this job. They are not intended to be an exhaustive list of all duties responsibilities and qualifications. Management reserves the right to change or modify such duties as required. Incyte Corporation is committed to creating a diverse environment and is proud to be an equal opportunity employer. We Respect Your Privacy Learn more at httpwww.incyte.comprivacy-policy The Incyte hiring organization processes your personal data to manage your job application in order to enter into an employment relationship with you if you are the successful candidate. During the process you may be asked to respond to questions that will screen out your application if you do not meet certain objective criteria required by the job. You can learn more about this process here. You may have the right to access delete restrict edit move or object to the use of your personal data. 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