The Gerencser lab at the Buck Institute seeks a Data Scientist in the field of microscopy-related image processing and machine vision. Dr. Akos Gerencser directs the Institute’s microscopy core, and the Gerencser laboratory uses cell biology, advanced microscopy, and single-cell gene expression techniques to address fundamental questions about mitochondrial function in health and aging. A current emphasis is the regulation of mitochondrial function in pancreatic β-cells in human type 2 diabetes. The successful candidate, in collaboration with other Buck laboratories, will solve a range of light microscopic, time-lapse, high-content and throughput, 3D, and whole slide imaging-related problems.
Working in a team environment, the Data Scientist will utilize various data analysis methods and software tools, building and implementing algorithms using relevant programming languages and computational environments in support of scientific projects. Modern microscopy image analysis extensively relies on AI-based (i.e., convolutional neural networks) and classical morphological image segmentation, object detection, instance segmentation, image registration, and object tracking. We use automated microscopes, and the amount of generated data requires largely automated workflows and analysis pipelines. You will help develop such tools and assist biologists in applying these methods.
The main project uses microscale bioenergetic assaying of human primary β-cell cultures, top-down analysis of cellular energy metabolism, and single-cell gene expression analysis. These require data analysis workflows combining multiple detection modalities. You will be involved in handling/programming data acquisition automation, such as high-content imaging and high-throughput screening/robotics systems. You will receive training in the experimental technologies used in this project, design and conduct experiments, and analyze data.
- MS in computer science or bioinformatics
- Experience in biological image processing
- Programming in Python, experience with common scientific imaging libraries
- Data analysis skills, such as programming in MATLAB, Mathematica, or R
- UNIX/Linux skills
- Proven portfolio or publication record
- Strong written and oral communication skills
- Ability to prioritize and manage your time
- Ability to work independently and successfully within a group
- Experience with laboratory automation
- Experience in single-cell RNAseq workflows and handling NGS data
- Deep learning, using convolutional neural networks for object detection, instance segmentation, or embedding
- Microscopy and image analysis using scripting
COMPENSATION & BENEFITS
- The starting salary for a new Scientific Data Analyst/Programmer is $90,000 in 2023, with a range of up to $130,000.
- Exciting, dynamic work environment at the forefront of science using state-of-the-art techniques.
- Generous benefits package including health insurance, paid parental leave, childcare assistance, generous vacation/sick leave, and 401(k) with 5% employer match.
- Collaborative environment – both for science and social activities.