Associate Director - Munich, Deutschland - AstraZeneca

AstraZeneca

Geprüftes Unternehmen

Munich, Deutschland

vor 3 Wochen

Geschrieben von:

Lena Wagner

beBee Recruiter

Beschreibung

The Computational Pathology team is growing to meet the challenges of pre-clinical and clinical big data generation initiatives in AZ Oncology with a focus on medical imaging.

Here exists an opportunity for a hard-working and motivated data scientist with strong expertise in biostatistics and/or spatial biology to join the team as an Associate Principal Scientist focusing on translating innovative image analysis features developed by our group into significant drug project impact.

ABOUT ASTRAZENECA

AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialisation of prescription medicines for some of the world's most serious diseases.

But we're more than one of the world's leading pharmaceutical companies.

Our pioneering approach is identifying and treating patients earlier, focusing on early stage cancer trials and listening and evolving based on their needs.

SITE DESCRIPTION

Our Computational Pathology site in Munich is one of over 400 sites here at AstraZeneca, providing an environment where everyone feels comfortable and able to be themselves is at the core of AstraZeneca's priorities, it's important to us that you bring your full self to work every day.

To help you maintain your best self, here's a sneak peek into some of the things this site provides for you:

After-work events, Lunch & Learns, spacious environment, Balanced office working environment, events, childcare support and of course the Alps around the corner for hiking, biking and skiing.

BUSINESS AREA
Fulfilling our ambition to be world leaders in Oncology.

We are already the fastest growing team within AstraZeneca and across the industry, and there are countless new indications and targets in our game-changing pipeline.

We have established a collaborative research initiative that brings together seven of the world's foremost oncology medical centres, to expedite research in some of the hardest-to-treat cancers.

What you'll do

Work as part of multidisciplinary teams spanning digital pathology, bioinformatics and translational medicine to understand their scientific and technical challenges and proactively impact these.
Generate tissue biomarker data to guide indication selection and identification of targeted patient populations and deliver biomarkers for clinical studies based on the best available computational pathology technologies
Discover, design, and implement innovative ways to identify and visualise meaningful patterns in complex spatial data.
Work with our bench scientists to proactively influence the generation of data assets as part of a data generation strategy.
Share code and train peers and bench scientists in the tools critical to interpreting complex data.
Conduct scientific project meetings to follow progress and present the scientific progress in Translational Medicine leadership meetings, governance boards and in project team meetings and ensure the quality of Translational Medicine clinical study reports, data reviews and interpretations, presentations, scientific publications and recommendations to development teams and management
Lead and champion new innovations within own discipline and assess existing processes and workflows for ongoing technology and/or workflow improvements which will aid the department to meet overall strategic objectives.

Essential for the role

PhD in Biological Sciences, Computational Biology, Bioinformatics, and/or related fields.
Expertise in one or more of the following; i) a deep understanding of the molecular mechanisms driving cancer or immunological disorders; ii) biomarker discovery for patient stratification, treatment response prediction and timetoevent modelling; iii) Experience in the design and analysis of randomised controlled trials, clinical trials, and other research studies.
Experienced at working on data analysis methods (using e.g. Python/R) in an academic or pharma research environment and applied knowledge on clinical biostatistics e.g. survival analysis, correlation, feature selection, crossvalidation and visualization.
Experience contributing to the research community through publication, conferences, and opensource code projects.
Strong leadership and oral/written communication skills, interpersonal skills, and ability to multitask a dynamic portfolio of drug projects and a robust technology development capability.
Strong publication record and proven communication and presentation skills to wide audience (specialists and nonspecialists).
Excellent problemsolving skills with clear understanding of the balance of innovation, smart risks, fitforpurpose solutions, and timely project delivery
Ability to drive, influence, manage, execute, and deliver results for complex multifunctional, interdisciplinary, and international projects.
Ability to act as an external ambassador and to influence external organizations