Software Engineer - Computational Pathology (m/f/d)

About

For our ambitious and growing Computational Pathology team at AstraZeneca Computational Pathology GmbH, we are looking for a software developer with a background in machine learning (ML) and data handling workflows. The group aims to establish a pipeline of computational pathology-based scoring methods. We aim to improve clinical outcome and transform traditional practice in the future and develop a first in-class computational pathology-based Diagnostics (Dx) product and establishing AstraZeneca as a market leader in AI-based Dx solutions with clinical utility.

The position is initially limited to one year.

Role

In your role you will support the development of computational pathology workflows through tool development and workflow automation. The role requires working cross-functionally with different computational pathology functional groups as well as external stakeholders. In this role you will support development of computational pathology workflows by:

• Working cross-functionally to collect and understand user requirements, establish workflow designs and efficient software solutions.

• Developing novel, or improve existing tools used in the computational pathology workflows.

• Add new features, fix bugs, raise test coverage and improve documentation and work towards ensuring compliance of processes and developed tooling.

Desired Profile

Education

Bachelor’s or Master’s degree in computer science / bioinformatics, computational biology, or a related field. Equivalent work experience in a data management role within the healthcare, clinical, or biotechnology sectors is highly desirable.

Experience

• Minimum of 3-5 years of experience in data management, preferably within a healthcare, clinical, or computational pathology environment.

• Demonstrated experience working with imaging data, clinical trial data, or similar multi-source datasets.

Technical Skills

• Python (excellent, required), TypeScript/Node/JavaScript (desirable), Go (nice to have)

• Software engineering best practices, with the aim of writing high performant, modern, bug-free code, proper documentation of code, unit-testing, code quality, etc. (required)

• TensorFlow, PyTorch (good working knowledge)

• Frameworks such as Keras, PyTorch Lightning, Ignite (good working knowledge in any)

• Processing platforms, such as Kubeflow or Airflow (optional)

• Image processing/Computer Vision problems (highly recommended), e.g. experience with OpenCV (optional)

• Acceleration frameworks such as Numba targeting CPU/GPU (recommended)

• Cloud computing infrastructure, in particular AWS (recommended)

• Experience of working in a regulated environment, developing code under pre-set regulatory rules (nice to have)

Soft Skills

• Effective communication skills, both written and verbal.

• A collaborative mindset with the ability to build and maintain relationships with cross-functional teams, external partners, and stakeholders.

• Excellent organizational skills, with the ability to manage multiple datasets and projects simultaneously.

• Strong problem-solving and troubleshooting skills, with attention to detail in ensuring data quality and compliance.

Benefits

• Individual development opportunities and a focus on lifelong learning.

• A diverse, inclusive and unbiased work environment.

• Trust, appreciation and space for co-creation.

• Wellbeing and Mobility Benefits.

Date Posted

Closing Date

AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.