IMU Biosciences
IMU Biosciences
IMU Biosciences — клиникалық зерттеулерге, диагностикаға және дәрі-дәрмек әзірлеуге арналған жоғары өлшемді иммунология технологияларын әзірлейтін, Лондонда орналасқан биотехнологиялық компания. Оның мультиомикалық, жоғары өнімді платформасы көлемі 2 мл қан үлгісінен 100 миллионнан астам иммундық дерек нүктесін талдап, шамамен 2 500 иммундық жасуша ішкі жиынын нақты уақыт режимінде ажыратады. Нәтижесінде алынған популяция ауқымындағы иммундық деректер жиынтығы гемопоэздік дің жасушаларын трансплантациялауға арналған болжамды скрининг, ағзаларды трансплантациялау кезінде трансплантаттың қабылданбауын бағалау, сондай-ақ иммуноонкологияда емге жауап беру және жағымсыз құбылыстармен байланысты иммундық белгілер сияқты қолдану салаларын қолдайды. IMU Biosciences клиникалық зерттеу топтарымен, фармацевтикалық және биотехнологиялық компаниялармен, сондай-ақ диагностикалық серіктестермен бірлесіп, иммундық фенотиптеуді практикалық клиникалық және коммерциялық құралдарға айналдырады.

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.

Сипаттама

  • 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.

Талаптар

  • 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.

Артықшылықтар

  • 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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