Research Scientist: Machine Learning for Drug Discovery and Biodata

Accenture UK & Ireland; Dublin; Hybrid; EUR 90,000 - 130,000; Full time

Job summary

Accenture Labs BioInnovation in Dublin focuses on AI for life sciences, developing prototypes in genomic medicine and computational chemistry. The team collaborates across disciplines to showcase impact and publish findings.

The role requires strong ML/DL foundations, Python, and experience turning experiments into deployable prototypes, with a hybrid on-site work setup in Ireland.

Qualifications

• PhD in CS/Computational biology or equivalent.
• Strong ML and DL foundations.
• Python (NumPy) and PyTorch experience.
• Experience designing AI/ML research prototypes.
• Parallel computing and GPU-accelerated workflows.
• SQL and data ingestion experience.
• Linux OS and shell scripting.
• Git and issue tracking experience.
• Excellent English communication.

Responsibilities

• Design and implement AI research prototypes for the life sciences.
• Collaborate with peer researchers and engineers to turn experiments into prototypes.
• Develop ML models for de novo molecule generation and property prediction.
• Design deep learning architectures for molecular generation and optimization.
• Work with multi-omics data and build data pipelines.
• Build data ingestion pipelines for large-scale biochemical and multi-omics datasets.
• Propose new research directions aligned with team strategy.
• Collaborate with domain experts to integrate knowledge into models.
• Stay current with AI in drug discovery, computational chemistry, and bioinformatics.
• Write clean code and present results to technical and lay audiences.

Skills

Machine Learning

Deep Learning

Python

PyTorch

Research Prototypes

GPU/Parallel Computing

SQL

Linux

Git

Teamwork

Education

PhD in Computer Science/Computational Biology/Computational Chemistry

Tools

NumPy

Git

Linux

Shell scripting

Job description

Location: Dublin, Ireland

Team: Accenture Labs Bioinnovation

Level: CL8

Type: 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 English

Optional 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.
• Familiarity with common genomic data formats (e.g., FASTQ, VCF).
• Experience processing Electronic Health Record (EHR) datasets.
• Familiarity with Knowledge Graph technologies a plus, but not a hard requirement (e.g. RDF, RDFS/OWL, SPARQL, triplestores, Neo4j).
• Expertise in back-end development (e.g. Django, Flask)
• Previous contributions to open-source projects in the machine learning, bioinformatics or computational chemistry space.