Computational Scientist - Single-Cell Algorithms

Job Description

Job Description

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.

New career opportunities

Members of PTI will be supported with industry-level resources to lead research projects and disseminate their discoveries and innovations to the broader biomedical community through frequent publications, presentations, and submissions to public data portals.

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.

Responsibilities :

• Develop and adapt pre-processing algorithms for mitigation of data collection artifacts
• Work with biological project leads to define hypotheses and apply appropriate statistical framework
• 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
• 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

Qualifications :

Preferred Qualifications :

We offer :

We aim to help fill a structural gap in today's R&D system. We enable fundamental research that requires unusual levels of scale and coordination yet is not rapidly monetizable by industry. We’re bringing together top talent from academia, industry, and startups to build a new model for innovative R&D. As an incubator within the Schmidt Futures Network, we identify high-impact scientific or technical research and development opportunities, ultimately defining and launching these projects as Focused Research Organizations.

We are an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. We do not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military or veteran status, or any other characteristic protected by applicable local, state, or federal law or company policy. We strive for a healthy and safe workplace and strictly prohibit harassment of any kind.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.