Senior Research Data Scientist - Cambridge, United Kingdom - Wellcome Sanger Institute

Wellcome Sanger Institute

Verified Company

Cambridge, United Kingdom

3 weeks ago

Posted by:

Tom O´Connor

beBee Recruiter

Description

Do you want to help us improve human health and understand life on Earth? Make your mark by shaping the future to enable or deliver life-changing science to solve some of humanity's greatest challenges.

About the Role:

You will be expected to work on and lead specific data science projects at the intersection of single-cell biology and machine learning.

You will work with open-source software and propose, develop, and maintain new solutions to analyze and interpret large-scale single-cell datasets.

You will join an interdisciplinary team of life scientists, computer scientists, and mathematicians.

We all learn from each other and work together to deliver the ambitious research goals within the Cellular Genetics Programme and support the Sanger Institutes' mission to "use information from genome sequences to advance understanding of biology and improve health.

"

You will be responsible for:

Independently manage and lead machine learning research projects and write outcomes in a scientific publication for submission to journals or machine learning conferences (ICLR, ICML, CVPR, etc).
Work with Ph.

students and postdocs in collaborating teams on developing solutions for interdisciplinary scientific problems in biology, providing supervision and training to junior members of the team.

Contribute to writing scientific papers on biotechnology and biology.
Distill your developed solutions into opensource and easytoinstall packages with documentation that facilitates the usage of your solution for downstream users, including biologists and bioinformaticians.
Present your research and analysis pipelines to internal and external audiences.

About You:

You will be supported in your personal and professional development and have the opportunity to lead peer-reviewed publications around using genetics and genomics approaches to guide drug discovery and present them at national and international conferences.

Essential Skills:

MSc and/or Ph.

D. or equivalent experience in a relevant quantitative discipline (e.g., Computer Science, Computational Biology, Genetics, Bioinformatics, Physics, Engineering, or Applied Statistics/Mathematics)

Proven experience using advanced statistical techniques, machine learning, and modern deep learning techniques.
Previous ML work experience in scientific/academic environment (RA/Internships are considered as work experience)
Strong knowledge of Python, including core data science libraries such as Scikit-Learn, SciPy, TensorFlow, and PyTorch.
Knowledge of software development good practices and collaboration tools, including gitbased version control, python package management, and code reviews.
Excellent communication skills, with the ability to explain complex machine learning algorithms and statistical methods to nontechnical stakeholders.
Experience working with cloud environments and tools, such as Amazon AWS S3, EC2, etc
Evidence of related work experience as a researcher in the area of Machine learning
Strong publication record, first author position ideal
Ability to quickly understand scientific, technical, and process challenges and breakdown complex problems into actionable steps
Ability to work in a frequently changing environment with the capability to interpret management information to amend plans
Ability to prioritize, manage workload, and deliver agreed activities consistently on time
Demonstrate good networking, influencing and relationship building skills
Strategic thinking is the ability to see the 'bigger picture
Ability to build collaborative working relationships with internal and external stakeholders at all levels
Demonstrates inclusivity and respect for all

Relevant publication of the groups:

-
Lotfollahi, M., Naghipourfar, M., Luecken, M. D., Khajavi, M., Büttner, M., Wagenstetter, M., Avsec, Ž., Gayoso, A., Yosef, N., Interlandi, M. & Others. Mapping single-cell data to reference atlases by transfer learning. Nature Biotechnology
-
Lotfollahi, M., Wolf, F. A. & Theis, F. J. scGen predicts single-cell perturbation responses. Nature Methods 16,
-
Lotfollahi, M., Rybakov, S., Hrovatin, K., Hediyeh-Zadeh, S., Talavera-López, C., Misharin, A. V. & Theis, F. J. Biologically informed deep learning to query gene programs in single cell atlases. Nature Cell Biology

Other Information:

Salary per annum:
£43,597-£51,794 (dependent upon skills and experience).

Application Process:

Please upload your current CV and a Cover letter outlining how you meet the criteria set out above.

Closing Date: 13th October 2023

Working at Wellcome Sanger:

Our flexible-hybrid working environment is designed to support a healthy work-life balance.

This means you can work flexibly with a combination of working from home, and working from our Campus to allow you to focus on being productive and part of the team while enjoying the benefits of working flexibly.

We aim to attract, recruit, retain and develop talent from the widest possible talent pool, thereby gaining insight and access to different markets to generate a greater impact on the world.

We have a supportive culture with the following staff networks, LGBTQ+, Parents and Carers and Race Equity to bring people together to share experiences, offer specific support and development opportunities and raise awareness.

The networks are also a place for allies to provide support to others.

We want our people to be whoever they want to be because we believe people who bring their best selves to work, do their best work.

That's why we're committed to creating a truly inclusive culture at Sanger Institute.

We will consider all individuals without discrimination and are committed to creating an inclusive environment for all employees, where everyone can thrive.

Our Benefits:

We are proud to deliver an awarding campus-wide employee wellbeing strategy and programme.

The importance of good health and adopting a healthier lifestyle and the commitment to reduce work-related stress is strongly acknowledged and recognised at Sanger Institute.