At AstraZeneca we put patients first and strive to meet their unmet needs worldwide. Working here means being entrepreneurial thinking big and working together to make the impossible a reality. If you are swift to action confident to lead willing to collaborate and curious about what science can do thenyoureour kind of person.
Recognizing the importance of individualized flexibility our ways of working allow employees to balance personal and work commitments while ensuring we continue to create a strong culture of collaboration and teamwork by engaging face-to-face in our offices3 days a week. Our headofficeispurposely designed with collaboration in mind providing space where teams can come together to strategize brainstorm and connect on key projects.
Our dedication to sustainability is also central to our culture and part of what makes AstraZenecaa great placeto work. We know the health of people the planet and our business are interconnected which is whyweretaking ambitious action to tackle some of the biggest challenges of our time from climate change to access to healthcare and disease prevention.
Introduction to role:
Are you ready to transform multi-omic complexity and AI-driven insights into targeted cancer medicines that change patient outcomes As a Senior Scientist focused on drug conjugates you will bridge advanced computation and wet-lab validation to discover novel targets decode mechanisms of action and deliver predictive biomarkers that guide clinical decision-making. Your work will directly influence which programs advance and how we match therapies to the patients most likely to benefit.
You will join a fast-moving oncology team with a bold pipeline spanning multiple indications. Partnering closely with experts across biology chemistry data science and clinical development you will convert complex datasets into testable hypotheses design decisive experiments and translate results into strategies for patient selection and combination therapy. Do you thrive at the interface of computation and experiment turning insights into decisive actions
Accountabilities:
Bioinformatics Discovery: Mine and integrate diverse datasets (public consortium proprietary clinical) to identify novel targets predictive biomarkers rational combinations and optimized dosing strategies.
Multi-omics Sample Generation: Oversee high-quality sample generation for RNASeq scRNASeq ATACSeq proteomics and phospho-proteomics to ensure reliable downstream analysis.
Cancer Signaling Interpretation: Apply deep knowledge of cancer signaling pathways to interpret proteomic and trhifts that reveal mechanisms and vulnerabilities.
Single-Cell Analytics: Analyze and interpret high-dimensional scRNASeq data to uncover cellular heterogeneity and generate tractable biological hypotheses.
Spatial and Transcriptomic Study Leadership: Design and analyze single-cell and spatial transcriptomic studies to map the molecular landscape of the tumor microenvironment.
AI/ML for Mechanism of Action: Utilize AI/ML tools to elucidate mechanisms of action for therapeutics with emphasis on antibody-drug conjugates.
Target Identification and Strategy: Identify clinically relevant tractable targets across hematologic and solid tumors and propose comprehensive intervention strategies.
Biomarker Development: Develop robust molecular signatures and biomarkers predictive of response versus resistance to optimize patient stratification across tumor types.
Clinical Reverse Translation: Reverse translate key clinical findings to inform and refine predictive in vitro preclinical models in both heme and solid tumors.
Translational Integration: Translate bioinformatics-derived findings into laboratory experiments to progress projects propose new targets and support go/no-go decision-making.
Data Package Delivery: Deliver high-quality data packages that define mechanism of action and therapeutic efficacy and inform portfolio strategy.
Microscopy Validation: Use advanced microscopy including fluorescence-based live-cell imaging and immunofluorescence staining to validate computational predictions.
Essential Skills/Experience:
Candidate must hold a minimum of 1 year proven experience with a postdoctoral degree or a minimum of 3 years industry experience with a masters degree.
Sophisticated bioinformatics analysis and data mining across public datasets (e.g. TCGA CCLE) large consortium datasets and proprietary clinical data to identify targets biomarkers combination partners and dosing regimens.
Oversight of high-quality sample generation for multi-omics pipelines including RNASeq scRNASeq ATACSeq proteomics and phospho-proteomics.
Expertise in cancer cell signaling pathways to interpret proteomic and transcriptomic changes.
Proven ability to analyze and interpret high-dimensional single-cell RNASeq to uncover heterogeneity and produce actionable hypotheses.
Experience leading design and analysis of transcriptomic studies including single-cell and spatial approaches to map the tumor microenvironment.
Utilization of AI/ML tools to elucidate mechanism of action for therapeutics specifically ADCs.
Identification of clinically relevant tractable drug targets in hematologic and solid tumors and development of comprehensive intervention strategies.
Development of robust molecular signatures and biomarkers predictive of performance versus resistance to optimize patient stratification in heme and solid tumors.
Reverse translation of key clinical findings to inform predictive in vitro preclinical model development in heme and solid tumors.
Translation of bioinformatics findings into laboratory experiments to advance project goals propose new targets and inform go/no-go decisions.
Delivery of high-quality data packages that define mechanism of action and therapeutic efficacy in heme and solid tumors.
Advanced microscopy skills including fluorescence-based live-cell imaging and immunofluorescence staining to validate computational predictions.
Desirable Skills/Experience:
Ph.D. in Bioinformatics Computational Biology Cancer Biology or a related field.
Practical experience with ADC target selection criteria linker/payload considerations and resistance mechanisms.
Proficiency in R and/or Python workflow management (e.g. Snakemake Nextflow) version control and scalable/cloud computing for multi-omic analytics.
Experience with spatial transcriptomics technologies and image analysis workflows that integrate with single-cell data.
Familiarity with building predictive biomarker models and patient stratification algorithms and validating them in preclinical systems.
Strong cross-functional communication scientific storytelling and the ability to influence decision-making with clear data narratives.
Prior leadership in cross-disciplinary studies that connect computation assay development and disease biology to deliver decision-grade data.
When we put unexpected teams in the same room we unleash bold thinking with the power to
inspire life-changing -person working gives us the platform we need to connect work at pace and challenge
perceptions. Thats why we work on average a minimum of three days per week from the office. But that doesnt mean were not flexible. We balance the expectation of being in the office while respecting flexibility. Join us in our unique and ambitious world.
The annual base pay (or hourly rate of compensation) for this position ranges from108473.6 to 162710.4 positions offer eligibility for various incentivesan opportunity to receive short-term incentive bonuses equity-based awards for salaried roles and commissions for sales roles. Benefits offered include qualified retirement programs paid time off (i.e. vacation holiday and leaves) as well as health dental and vision coveragein accordance withthe terms of the applicable plans.
As AstraZeneca continues to put patients at the forefront of our mission we are excited for our move to Kendall Square/Cambridge in2026. Find out more information here:Kendall Square Press Release
AstraZenecais an equal opportunity employer that is committed to diversity and inclusion and providing a workplace that is free from discrimination. AstraZeneca is committed to accommodating persons with disabilities. Such accommodation is available on request in respect of all aspects of the recruitment assessment and selection process and may be requested by emailing.
Why AstraZeneca:
Here ambitious science meets real-world impact. You will work in an environment that pairs cutting-edge platformsmulti-omics single-cell and spatial technologies AI/ML and advanced imagingwith a pipeline that moves decisively from discovery to the clinic. We bring diverse specialists together to ask bold questions pressure-test ideas and accelerate progress against some of the hardest-to-treat cancers valuing kindness alongside ambition so you can stretch your skills while making a tangible difference for patients.
Where can I find out more
#LI-Hybrid
Date Posted
27-Jan-2026Closing Date
14-Feb-2026Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and furtherance of that mission we welcome and consider applications from all qualified candidates regardless of their protected characteristics. If you have a disability or special need that requires accommodation please complete the corresponding section in the application form.
Required Experience:
Senior IC
AstraZeneca is an equal opportunity employer. AstraZeneca will consider all qualified applicants for employment without discrimination on grounds of disability, sex or sexual orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, ... View more