Laboratory Scientist, Genomics, DeepMind Science Lab at The Francis Crick Institute (Fixed Term Contract)
Location
London, UK
Level
Senior
Department
Research
Type
Full - Time
Salary
Job Description
Posted on:
January 13, 2023
DeepMind is looking to hire a laboratory research scientist (LRS), specialising in the broader field of genomics, on a one year contract. The primary responsibility of the role is to collaborate with computational teams to conduct biological experiments in an end-to-end manner, from initial experimental design to final data collection. The ideal candidate will also provide support across the fields of molecular biology, biochemistry and structural biology, as part of a fundamental research program at the intersection of biology and ML.
Responsibilities
- Independent design, implementation, and execution of high throughput experiments in human cells and model organisms.
- Cell profiling through transcriptomics, proteomics, or cell biological assays.
- Cell biological assay development.
- Experimental iteration with machine learning experts.
- Scientific and technical support of projects in the lab.
- Training of junior researchers in laboratory techniques.
- Communicate progress updates with non-experts and team members from a diverse group of backgrounds (e.g. management, research engineers).
- See opportunities to improve empirical data generation and drive innovation, keeping abreast of relevant high-throughput assays, standards and technologies.
Job Requirements
- PhD in a relevant biological field (e.g. genetics, cell biology, molecular biology) or equivalent industry experience in R&D.
- Extensive hands-on wet lab experience in academia or industry with demonstrated experience in R&D. In particular, practical experience with multiplex assays coupled with high-throughput next-generation sequencing.
- Proven experience with high-throughput genome editing.
- Experience with a range of molecular biology techniques (DNA, RNA extraction, PCR and RT-qPCR as well as cell-based biochemical assays such as flow cytometry).
- Ability to design and optimise phenotypic screens in eukaryotic cells.
- Excellent attention to detail and experience with high calibre troubleshooting and producing reliable data.
- Experience in a research environment with an established record of efficiency.
- Proven ability to work effectively within a team with ability to multi-tasks and coordinate own workload.
- Skilled in collaboration with computational biologists.
- Excitement about the application of Machine Learning to fundamental problems in biology.
