AstraZeneca
2 days ago
Senior Scientist, AI for Translational Sciences
Sign up to save this job, get alerts, and apply with an optimized CV.
Company information
- Company
- AstraZeneca
- Location
- España, Cataluña, Barcelona, Barcelona Spain
- Posted
- 2 days ago
Job description
Role Based in Barcelona : 3 days onsite/2 days work from home. Are you a specialist in AI/ML for molecular data analysis and exploratory biomarker discovery? Are you leveraging machine learning models with molecular data in your daily work? Do you want to make a significant impact on Oncology & Biopharmaceuticals R&D by applying your knowledge in a company that transforms scientific ideas into life-changing medicines? If so, AstraZeneca could be your next career destination! Accountabilities: Join our growing AI for Translational Sciences team to support AstraZeneca strategic initiatives in machine learning and bioinformatics analysis of molecular data, including DNA sequencing, single-cell and bulk transcriptomics, proteomics, spatial, and digital pathology. As an ML/AI bioinformatician with expertise in NGS omics data, you'll design and apply innovative computational & AI analysis methods to advance our research portfolio. Working within a team and maintaining the highest quality standards, your strong quantitative skills will help build AI modelling solutions and agentic systems to interrogate diverse molecular datasets, empowering researchers to use AI systems for data-driven decision-making, translational science, and biomedical knowledge generation. Essential Skills/Experience:
- Master’s degree in Bioinformatics, Computational Biology, Machine Learning, or a related field with 4+ years of applied experience in ML/AI molecular data analysis; or Ph.D. in Bioinformatics, Computational Biology, Machine Learning, or a related field
- Expertise in AI/ML modelling approaches to molecular (omics, imaging) data
- Strong statistical and model-evaluation skills, including appropriate baseline selection, patient-level and cross-study validation, prevention of data leakage, handling of confounding and batch effects, and assessment of uncertainty and generalisability
- Hands-on experience implementing and adapting deep-learning models using frameworks such as PyTorch, transformers, huggingface_hub
- Deep understanding of at least one type of molecular profiling data (e.g. RNA or DNA sequencing) and experience in analysing human Illumina NGS data
- Understanding of drug discovery biology: target identification, target validation, mechanism of action, or translational science
- Experience using AI tools/agentic frameworks like coding copilots and research assistants
- Proven programming skills (Python essential) and familiarity with software development best-practices (end-to-end tests, unit testing, version control with git)
- Experience working in Unix/Linux environments, familiarity with package management (e.g. Conda)
- Cloud computing (preferably AWS) or High-Performance Computing (HPC)
- ‘Builder’ mindset, strategic thinker, and experience leading projects
- Strong, professional communication skills and excellent attention to detail, capable of developing effective collaborative relationships with diverse teams of technical and non-technical analysts, engineers, scientists, strategists
- Experience working within a team environment
- Experience working with patient data from clinical trials and biomarker development
- Experience with biological foundation models such as BulkFormer, scGPT and DNABERT
- Understanding of modern deep learning architectures such as Transformers, CNN and GRU
- Experience with exploring explainability of deep learning models on multi-omics data
- Well networked within external bioinformatics, NGS, and AI/ML communities
- Experience working in pharma or biotech R&D
Required skills
- attention to detail
- communication skills
- ai
- inclusion
- python
- aws
- machine learning models
- pytorch
- git
- unit testing
- imaging
- r&d
- version control
- diversity
- unix/linux environments
- oncology
- cloud computing
- master’s degree
- data-driven decision-making
- ml
- transformers
- team environment
- clinical trials
- project leadership
- pharma
- ai tools
- equality
- explainability
- patient data
- engineers
- wearables
- strategic thinker
- hpc
- spatial
- gru
- bioinformatics
- ngs
- high-performance computing
- ph.d.
- patient-centric
- digital pathology
- patient outcomes
- healthcare provider
- package management
- computational biology
- end-to-end tests
- uncertainty
- proteomics
- cnn
- conda
- collaborative relationships
- biopharmaceuticals
- technical analysts
- non-discrimination
- perspectives
- scientists
- digital therapeutics
- agentic systems
- dna sequencing
- visual analytics
- deep-learning models
- omics
- work authorization
- data leakage
- strategists
- coding copilots
- deep learning architectures
- biomarker discovery
- translational science
- employment eligibility verification
- target identification
- computational analysis
- research assistants
- biological foundation models
- statistical skills
- mechanism of action
- multi-omics data
- single-cell transcriptomics
- bulk transcriptomics
- biotech r&d
- batch effects
- target validation
- molecular data analysis
- translational sciences
- bioinformatician
- ngs omics data
- ai analysis methods
- ai modelling solutions
- molecular datasets
- biomedical knowledge generation
- ai/ml modelling
- model-evaluation skills
- baseline selection
- patient-level validation
- cross-study validation
- confounding effects
- generalizability
- huggingface_hub
- rna sequencing
- illumina ngs data
- drug discovery biology
- software development best-practices
- non-technical analysts
- biomarker development
- bulkformer
- scgpt
- dnabert
- external bioinformatics
- ai/ml communities
- integrated data
- next generation products
- cutting-edge innovations
- industry-leading skills
Interested in this position?
Create your free account and tailor your CV to match this job.