Parallel Squared Technology Institute (PTI) is a non-profit research institute aiming to catalyze a leap in protein analysis technology and use it to explore new biological frontiers. PTI supports open research and educational opportunities supporting rapid career development for scientists, engineers, and mathematicians.
Why? Protein dysfunctions directly cause many diseases, such as Alzheimer’s disease. Yet, proteins remain understudied because of technological hurdles.
How? To resolve these limitations, PTI will develop mass tags enabling a new framework for multiplexed protein analysis by mass spectrometry towards achieving 100-fold increase in throughput. Scientists at and collaborating with the institute will use these gains to directly investigate disease mechanisms and resolve problems that have proven intractable for decades. Our proof of principle technology and strategies are outlined at: parallelsq.org.

SUMMARY OF POSITION

We are looking for an individual contributor with previous experience in ‘omics data interpretation, who will lead the design and development of new computational analysis pipelines. This position will involve analyses of mass spectrometry proteomics data in order to infer biological mechanisms at play in either the Alzheimer’s Disease or Immuno-Proteome Aging projects at PTI. The successful candidate will work in a highly interdisciplinary team environment with other scientists. In order to be seriously considered for this position, we require a cover letter as part of the candidate’s application.

QUALIFICATIONS:

• Master’s with at least 5 years of relevant experience, or PhD in Computational Biology, Bioinformatics, or related field.
• Experience in large-scale analyses that involve many samples, such as thousands of single cells or bulk tissues.
• Proficiency in analyzing and visualizing datasets with Python and/or R as well as the command line.
• Proficiency in good practices for reproducible research using tools such as git, Jupyter notebooks, etc.
• Highly organized with strong analytical and coding skills.
• Experience with cloud environments such as AWS or Google Cloud.

PREFERRED QUALIFICATIONS:

• Experience with mass spectrometry proteomics.
• Experience in designing, developing, and maintaining bioinformatic pipelines for single cell and bulk ‘omics data.
• Experience using packages such as Seurat, bioconductor, DESeq2, ComBat, Scanpy, LIGER, and/or other.
• Experience integrating multiomics data.

• Design and develop optimized analysis pipelines for large ‘omics datasets.
• Perform deep and detailed analyses for data-intensive experiments with team members and communicate interpretable results.
• Hands-on development of interactive tools for data interpretation of high throughput proteomics datasets for other team members using RShiny, Python, D3, or other tools.
• Assist team members in searching and interpreting proteomics raw data.
• Update different software tools for team members as needed.
• Curate large-scale datasets for internal and external usage.
• Mentor scientists and research associates.
• Prepare internal reports and manuscripts as well as present results at internal or external scientific meetings as appropriate.
• Demonstrate a commitment to diversity, inclusion, and cultural awareness through actions, interactions, and communications with others.
• Other duties as assigned.