Job Description

Summary
The laboratory of Dr. Sethu Pitchiaya seeks to hire a research computer scientist to work at the intersection of biological image analysis and bioinformatics. Our work is highly interdisciplinary and lies at the intersection of RNA biology, pathology and technology development. We develop and deploy spatial-resolved, single-cell and single-molecule imaging to interrogate gene regulatory mechanisms at high-throughput and high-resolution, especially in the context of cellular stress response and cancer. The hired individual will work with a highly motivated team of scientists, engineers and clinicians on a wide range of projects that span both basic and translational sciences. S/he will be expected to develop image analysis modules, especially for spatial omics and high-content screening, and generate informatic pipelines to perform statistical analysis of the ensuing datasets. Individuals with additional experience in analyzing next-generation sequencing datasets (including bulk/single-cell genomics, epigenomics and transcriptomics) will be highly preferred. The individual is also expected to have excellent organizational skills, multi-tasking and problem-solving ability, interpersonal and communication skills, and ability to meet deadlines with a high degree of accuracy. S/he should possess attention to detail, motivation to learn new things and ability to adapt to changing needs of the lab. A commitment of 12 months to the job will be required, with the possibility of the position being extended beyond this time frame upon mutual agreement.

We are committed to fostering a diverse and inclusive work environment, which supports individual development and collaborations. We encourage applications from under-represented minorities, including women, individuals from disadvantaged backgrounds, under-represented racial or ethnic groups, and individuals with disabilities. We will make every effort to remove any barriers to the success of the hired individual. For further details about this position, please send an email to [email protected].

Mission Statement
Michigan Medicine improves the health of patients, populations and communities through excellence in education, patient care, community service, research and technology development, and through leadership activities in Michigan, nationally and internationally. Our mission is guided by our Strategic Principles and has three critical components; patient care, education and research that together enhance our contribution to society.

Responsibilities*
Develop image analysis modules, especially for spatial omics and high-content screening, and generate informatic pipelines to perform statistical analysis of the ensuing datasets. Individuals with additional experience in analyzing next-generation sequencing datasets (including bulk/single-cell genomics, epigenomics and transcriptomics) will be highly preferred. The individual is also expected to have excellent organizational skills, multi-tasking and problem-solving ability, interpersonal and communication skills, and ability to meet deadlines with a high degree of accuracy. Candidate should possess attention to detail, motivation to learn new things and ability to adapt to changing needs of the lab.

Required Qualifications*
1. Master’s or higher level education in data science, computer science, applied mathematics or biomedical science with 2+ years of experience.
2. Extensive experience in biological image analysis. Familiarity with feature detection and computer vision concepts, especially image segmentation and pixel classification methods will be required.
3. Proficiency in Python, MATLAB and R.
4. Experience with using Cellprofiler and ImageJ, especially writing custom modules for Cellprofiler and custom macros/plugins for ImageJ.
5. Ability to implement high-performance/parallel computing and version control.

Desired Qualifications*
1. A Ph.D. degree in data science, computer science, bioinformatics or biophysics.
2. Experience in analyzing single-molecule, spatial omics, high-content screening or single-cell sequencing data.
3. Experience in designing, developing, and maintaining bioinformatic pipelines for bulk genomic and transcriptomic datasets.
4. Expertise in OpenCV, artificial intelligence and machine learning tools for image analysis.