Merck

Director of foundational AI at Merck, leading a team of ML researchers and engineers to develop and train large multi-modal foundation models and bespoke methods for biological data analysis. The role involves providing technical guidance, interpreting results, and publishing research findings, with a focus on advancing therapeutic strategies. Requires a PhD and significant experience in ML/AI, team leadership, and training large models.

Senior AI Research Scientist at Merck in Prague, focusing on research, assessments, and technical evaluations of AI models and frameworks to solve problems and enhance generative AI capabilities. The role involves conducting feasibility studies, creating proof of concepts, and leading smaller projects, with an emphasis on applying AI to internal problems and datasets within the biopharmaceutical domain.

Seeking a Scientist, MCICC to drive innovation in AI-powered drug evaluation and development. This role focuses on building and optimizing advanced AI systems, including large language models (LLMs) and molecular generation and property prediction models. The ideal candidate will combine deep technical expertise with domain knowledge in pharmaceutical R&D, enabling rapid iteration and deployment of cutting-edge solutions.

AI Research Scientist with 1-2+ years of experience in healthcare IT, focusing on research, assessments, and technical evaluations of AI models and frameworks to solve internal problems and enhance generative AI capabilities. The role involves creating proof-of-concepts, staying updated on AI research, and mentoring colleagues. Requires a strong understanding of AI research landscape, hands-on Python development, and familiarity with GenAI, deep learning, NLP, CV, and ML frameworks, preferably within a cloud environment.

Merck is seeking a computational biologist with expertise in image analysis to join their Translational Genome Analytics research team. The role involves applying AI/ML-based analytics to large multi-omics imaging and functional genomics datasets for target and biomarker discovery in drug development, with a focus on Oncology. The candidate will collaborate with cross-functional teams and contribute to quantitative analysis of imaging datasets and integration of machine learning with phenotypic screens.