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IMU Biosciences
IMU Biosciences
11 – 50 Xodimlar
B2BBiotexnologiyaSog‘liqni saqlash
IMU Biosciences — Londonda joylashgan, klinik tadqiqotlar, diagnostika va dori vositalarini ishlab chiqish uchun yuqori o‘lchamli immunologiya texnologiyalarini yaratuvchi biotexnologiya kompaniyasi. Uning multi-omik va yuqori unumdor platformasi 2 ml qon namunasidan 100 milliondan ortiq immun ma’lumot nuqtalarini tahlil qiladi hamda taxminan 2 500 ta immun hujayra kichik to‘plamini real vaqt rejimida ajratib ko‘rsatadi. Natijada hosil bo‘ladigan populyatsiya miqyosidagi immun ma’lumotlar to‘plami gematopoetik ildiz hujayralari transplantatsiyasi uchun bashoratli skrining, parenximatoz a’zolar transplantatsiyasida transplantat rad etilishini baholash, shuningdek immuno-onkologiyada davolashga javob va nojo‘ya hodisalar bilan bog‘liq immun belgilar kabi yo‘nalishlarni qo‘llab-quvvatlaydi. IMU Biosciences klinik tadqiqot guruhlari, farmatsevtika va biotexnologiya kompaniyalari hamda diagnostika sohasidagi hamkorlar bilan hamkorlik qilib, immun fenotiplashni amaliy klinik va tijoriy vositalarga aylantiradi.
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Kompaniyadagi ish o‘rinlari

Bioinformatics Software Engineer – Flow Cytometry

Build and maintain regulated machine learning pipelines for flow cytometry at IMU Biosciences. The role covers annotation, model tracking, reproducibility, and compliance for a precision medicine platform.

GBBuyuk BritaniyaGibridTo‘liq stavkaO‘rta darajaSeniorTalab Qilinadigan Til: inglizchaDasturiy ta’minot muhandisiFull-stack muhandisi
DockerNumpyPandasPythonPyTorchScikit-Learn

Tavsif

  • Run automated cell annotation workflows on large cytometry datasets.
  • Produce cell membership files, cell subset ratio tables, and automated reports that flag outliers for quality control.
  • Apply locked automated gating ensembles to cross-validation and evaluation data partitions.
  • Track and document gating exposure metrics for each patient.
  • Set and lock baseline models and numerical stability criteria for flow cytometry feature extraction pipelines.
  • Maintain the formal model lifecycle registry, including versioning, freezing, and locking gating ensembles and candidate predictive models.
  • Refit shortlisted machine learning models on larger cohorts and freeze final models before blinded clinical evaluations.
  • Commit versioned code, pin Conda and Docker environment specifications, and log random seeds and model hyperparameters.
  • Act as the primary code reviewer across the computational pipeline.
  • Apply controls against data leakage, verify data integrity, and uphold modular coding standards.
  • Take part in Independent Method Reviews, traceability audits, and regulatory compliance checks.
  • Work with Machine Learning Engineers, Biostatisticians, and Clinical Scientists.
  • Report to the Lead Data Scientist.

Talablar

  • A master’s degree or Ph.D. in Bioinformatics, Statistics, Computational Biology, Computer Science, Bioengineering, or a related quantitative discipline.
  • At least three years of professional experience with high-throughput flow cytometry data in a regulated, academic, or biotech setting.
  • Fluency in Python and experience with NumPy, Pandas, SciPy, scikit-learn, and PyTorch.
  • Demonstrated use of software engineering practices, including Git, CI/CD, workflow managers such as Nextflow, Docker environment pinning, and ML artifact tracking.
  • Familiarity with flow cytometry feature generation and batch-effect harmonisation.
  • Familiarity with cross-validation leakage risks in high-dimensional flow cytometry predictive modelling.
  • Existing right to work in the UK.

Imtiyozlar

  • Competitive salary and company bonus scheme.
  • Pension.
  • Health insurance.
  • Life assurance.
  • Income protection.
  • A fast-paced, collaborative startup environment.
  • Opportunities for career development and progression.

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