The Spatial Biotechnology Group is looking for a talented and highly motivated Postdoctoral Researcher to work at the interface between experimental and computational biology, building automated, closed-loop workflows. The position is part of our effort to understand how cells spatially organize to drive solid tumor development, and it brings together three fast-moving fronts: spatial proteomics, lineage tracing technologies, and laboratory automation. The successful candidate will design and execute robot-driven experiments and will analyze the resulting spatial data, closing the loop between experimental design, automated execution and data-driven decisions about what to run next. This is an opportunity for a hybrid scientist who wants to help define how a self-driving biology laboratory works. Main tasks and

responsibilities:
Design, build and validate automated liquid-handling workflows on an Opentrons Flex platform (Python API). Establish and run spatial proteomics on in vitro co-cultures, engineered 3D tumor models and tissue sections. Implement clonal barcoding and lineage tracing readouts, including in situ detection and debarcoding of individual clones. Scale perturbation experiments to high-throughput formats, integrating robotics, automated microscopy and sample tracking into reproducible end-to-end pipelines. Develop and apply computational pipelines for image processing, cell segmentation, debarcoding and spatial statistics. Close the experimental-computational loop, using analysis results to guide the design of the next round of automated experiments (design of experiments, active learning). Ensure reproducibility and FAIR data practices: version-controlled code, documented protocols, structured metadata and open sharing of tools. Present results at internal meetings and international conferences,



and contribute to manuscript preparation. Apply for competitive postdoctoral fellowships and, later, for independent career awards, with full support from the group and from IBEC’s grants office in preparing the proposals. Collaborate closely with experimental and computational colleagues within the group and with external partners, and co-supervise students working on related tasks. Requirements for candidates: A PhD in life sciences, bioengineering, biotechnology, computational biology or a related discipline. Solid hands-on wet-lab experience (mammalian cell culture, molecular biology and/or imaging-based assays). Programming proficiency in Python and/or R. Demonstrated experience in the analysis of large imaging and/or omics datasets. Strong interest in laboratory automation and in making experiments scalable, traceable and reproducible. Ability to work independently, take initiative and solve complex problems across the experimental-computational interface. Willingness to work in a highly multidisciplinary environment. Competencies and skills needed: communication, teamwork, proactivity, commitment, integrity, time management, critical and analytical thinking, precision, and focus. Full professional proficiency in English (written and spoken). Advantageous: Hands-on experience with liquid-handling robots (Opentrons Flex or OT-2, Hamilton, Tecan) and their Python APIs. Experience with spatial proteomics (e.g.,



iterative immunofluorescence, PhenoCycler/CODEX, imaging mass cytometry, MIBI) or with spatial transcriptomics. Experience with DNA barcoding, lineage tracing, CRISPR screens or other high-throughput perturbation approaches. Experience with quantitative image analysis and deep learning tools for segmentation and classification (e.g., Cellpose, napari, scikit-image, PyTorch). Experience with 3D culture systems, organoids or microfluidic devices. Familiarity with workflow managers (Nextflow, Snakemake), containers (Docker, Singularity) and high-performance computing environments. Interest in AI-assisted experimental design, self-driving laboratories or foundation models for biological data. A background in cancer biology or immunology.

We Offer
Number of available positions: 1 Working

conditions:
Full time (37.5 hrs/week), open-ended contract for scientific and technical activities, linked to the project and budget duration. Salary according to qualifications and experience following IBEC pay scales. Measures to reconcile work and family life (parental leave, adaptable schedule

working hours
, 23 working days of paid holidays, 9 leave days for personal matters, among others). IBEC ensures equality of access to professional development opportunities irrespective of employment status, length at IBEC or other factors. The IBEC’s yearly training catalogue offers a wide range of training in technical and transferable skills including mobility grants and a Mentoring programme for predoctoral and postdoctoral researchers. Stimulating, interdisciplinary research and high-quality international scientific environment. Active support in the application for a personal fellowship (MSCA Postdoctoral Fellows

📌 Postdoctoral Researcher (Madrid)
🏢 Institute for Bioengineering of Catalonia (IBEC)
📍 Madrid