Research Scientist: Machine Learning for Drug Discovery and Biodata

# Research Scientist: Machine Learning for Drug Discovery and BiodataAccenture Federal ServicesLocation not specifiedFull-timeAI tools:PyTorchUpload your resume once and Scout applies for youApply with ScoutShare this job:LinkedInXSave imageYou will conduct machine learning research for life sciences in Accenture Labs BioInnovation, developing prototypes for drug discovery and analysis of multi-omics data. The work spans model design, data pipelines, experiments, and collaboration with research scientists and domain experts, with opportunities to publish and contribute to open source. Permanent Hybrid PhD Skills and expertisePythonPyTorchNumPyDeep learningGraph machine learningTransformersDiffusion modelsSQL Key responsibilities Develop machine learning models for molecule generation, property prediction, and multi-omics analysis. Build data ingestion pipelines for biochemical, genomic, and clinical datasets. Design experiments, interpret results with domain experts, and present research findings. How this job comparesCompared with 90 open mid-level research jobs on October 10, 2026.Similar open jobs: We Love AI Jobs lists 90 open mid-level research jobs at 53 companies.Remote work: This job is hybrid. 12 of the 90 mid-level research jobs (13%) are remote.AI in this role: High. AI is the core of the work: building, training or deploying AI systems. The role's core work is designing and implementing machine learning models and research prototypes for drug discovery and life sciences. It includes deep learning, molecular generation, and multi-omics analysis. Full descriptionLocation: Dublin, IrelandTeam: Accenture Labs BioinnovationLevel: CL8Type: Full-time, on-site (hybrid)About: This is an opportunity to play a key role in the Accenture Labs BioInnovation team, in Dublin Ireland.Accenture Labs BioInnovation is the biotech research arm of Accenture Labs and focuses on Artificial Intelligence, Bioinformatics, and Computational Chemistry with a strong emphasis on Machine Learning for Life Sciences.The lab is co-located with The Dock, Accenture's global center for innovation.We design and prototype new ideas that have a strategic impact on our clients' businesses. We offer a blend of industry-related research projects and academic-oriented activities, including an open publication policy and contribution to the open-source community.Job Description:• Design and implement AI research prototypes for the life sciences, including genomic medicine and computational chemistry.• Collaborate with peer research scientists and engineers and turn experimental methods and their output into full-fledged prototypes to showcase the impact of our research.• Develop and implement machine learning models for de novo molecule generation and property prediction (small molecules and biologics)• Design and optimize deep learning architectures for molecular generation and optimization (e.g., graph machine learning, transformers, diffusion models).• Design and implement machine learning prototypes tthat learn insights from multi-omics data (e.g. genomics, transcriptomics, proteomics).• Build data ingestion pipelines to process and analyze large-scale biochemical and multi-omics datasets (e.g., SMILES, PDB, proteomics, genomics, clinical records).• Propose novel research directions and align with the team's strategy.• Collaborate with subject matter experts to integrate domain knowledge into our AI models and interpret results.• Stay on top of the latest advancements in AI/machine learning, AI for drug discovery, computational chemistry, and bioinformatics.• Write clean, well-documented code. Design and execute experiments. Describe and present results to technical and lay audiences.Required qualifications and skillset:• PhD in Computer Science, Computer Engineering, Bioinformatics, Computational Biology, Computational Chemistry, Computational Genomics, or equivalent industry experience.• Strong Machine Learning and Deep Learning foundations.• Solid Python and Scientific Python programming skills (e.g. NumPy) and Machine Learning frameworks such as PyTorch.• Prior hands-on experience with AI/ML research prototypes design and development• Proven knowledge of parallel computing techniques for Python and GPU acceleration, to optimize model training and data processing workflows.• Solid experience with data engineering, data ingestion, relational databases management, SQL.• Working knowledge of Linux OS, shell scripting• Hands-on experience with git and popular issue tracking systems• Ability to work creatively and analytically in a problem-solving environment• Eagerness to contribute to a team-oriented environment• Excellent verbal and written communication in EnglishOptional skillset:• Practical experience with LLMs (frontier API-based and self-hosted/open-weight), including retrieval-augmented generation and in-context learning, PEFT (e.g., LoRA/QLoRA), and building agentic workflows.