Bioinformatics

Reed; Cambridge; Presencial; GBP 40.000 - 70.000; Jornada completa

Descripción de la vacante

Reed in Cambridge is seeking a Bioinformatician to join an innovative team focused on functional genomics, data science, and scalable analytics. You will tackle complex biological datasets, apply state‑of‑the‑art statistical methods and machine learning to research and product development, and collaborate with scientists to inform experimental design and interpretation.

The role emphasizes advancing genomics workflows, producing rigorous reports, and sharing knowledge across cross‑functional

Formación

• Proven track record in statistics, biostatistics, bioinformatics or genomics.
• Strong experience with ML, deep learning and statistical modelling.
• Advanced programming in Python and R (and optionally Julia).
• Experience with NGS/OMICS datasets and WGS workflows.
• Familiarity with bioinformatics databases and pipelines.

Responsabilidades

• Lead statistical and bioinformatics analyses on complex datasets.
• Develop statistical methods and computational algorithms.
• Apply ML/AI to research and product initiatives.
• Collaborate with lab scientists for experimental design and data interpretation.
• Analyze NGS and other high-throughput genomics data.
• Produce technical reports and present findings to stakeholders.
• Support knowledge sharing across research and technology teams.

Conocimientos

Statistics

Bioinformatics

Genomics

Machine Learning

Python

R

Herramientas

GitHub

TensorFlow

PyTorch

Scikit-Learn

Keras

Descripción del empleo

Bioinformatician

Are you a talented Bioinformatics Scientist with a passion for data science, machine learning, and genomics? We are seeking an ambitious and highly motivated individual to join an innovative research and technology team developing cutting-edge solutions in the field of functional genomics.

This is an exciting opportunity to work within a multidisciplinary environment, tackling complex biological data challenges and contributing to the development of advanced statistical and computational approaches that support scientific discovery and innovation.

Key Responsibilities

• Lead statistical and bioinformatics analysis projects, delivering meaningful insights from complex biological datasets.


• Develop and enhance statistical methodologies and computational algorithms.


• Apply machine learning and artificial intelligence techniques to research and product development initiatives.


• Collaborate closely with laboratory scientists to support experimental design, data analysis, and interpretation.


• Analyse, process, and interpret Next Generation Sequencing (NGS) and other high-throughput genomics datasets.


• Produce technical reports and present findings to internal and external stakeholders.


• Support knowledge sharing, mentoring, and cross-functional collaboration across research and technology teams.

Essential Experience and Qualifications

To be considered for this role, you must demonstrate:

• A proven track record in statistics, biostatistics, bioinformatics, genomics, or a related scientific discipline.


• Strong experience in machine learning, deep learning, and statistical modelling.


• Advanced programming skills in at least two of the following: Python, R, or Julia.


• Hands‑on experience using data science and machine learning libraries such as Pandas, NumPy, Scikit‑Learn, TensorFlow, PyTorch, Keras, or equivalent.


• Experience working with Next Generation Sequencing (NGS), OMICS datasets, or other large‑scale biological data.


• Knowledge of variant calling, exome sequencing, whole genome sequencing (WGS), or similar high‑throughput genomics workflows.


• Familiarity with bioinformatics databases, tools, and analytical pipelines.


• Experience using GitHub and version control systems in collaborative development environments.


• Strong data visualisation, statistical analysis, and problem‑solving capabilities.

Desirable Experience

Applications would be particularly welcomed from candidates with experience in:

• Hi‑C, Capture Hi‑C, HiChIP, or related 3D genomics technologies.


• Scientific Machine Learning (SciML).


• Biomarker discovery or target identification programmes.


• Bioinformatics pipeline development.

About You

You will be an inquisitive and analytical scientist who enjoys solving complex problems and translating data into actionable insights. You will thrive in collaborative environments, be comfortable working across multiple projects, and have the ability to balance immediate business needs with longer‑term research objectives.

If you are looking to play a key role in advancing innovative genomics research through data science, machine learning, and bioinformatics, we'd love to hear from you.