Staff Scientist II, Target Discovery, Screening, and Automation

Protagonist Therapeutics•Newark, NJ

15h•Onsite

About The Position

We are seeking an innovative, experienced, and collaborative individual to join the new Screening and Automation team in the Biology and Translational Science Unit in Drug Discovery at Protagonist Therapeutics. We are looking for a skilled Bioinformatician to play a crucial role at the intersection of high-throughput biology and computational data science. In this dynamic role, you will help scale functional screening assays and build automated data pipelines utilizing big data and Large Language Models (LLMs). Furthermore, you will play a key role in the early-stage pipeline by expanding the company’s bioinformatic capabilities key for integrating complex screening outputs, accessing and leveraging relevant human datasets to drive new target discovery, accelerate hit identification, and validate target mechanisms for immunologic, hematologic, and metabolic diseases. This position will report to the Director of Screening and Automation and work with teams across R&D in the U.S. and Australia.

Requirements

A Ph.D. in a relevant field such as biology, bioinformatics, computational biology, or engineering is required.
A minimum of 2 years of experience in the pharmaceutical or biotechnology industry.
Hands-on experience analyzing high-throughput screening (HTS) data, functional assays, and utilizing human genetic/genomic data for target discover.
Strong programming skills in Python and R.
Experience with relational databases (SQL) and big data computing environments (AWS, cloud computing).
Foundational experience applying machine learning or NLP/LLM techniques to biological data challenges.
Self-starter mentality with a knack for identifying bottlenecks in data pipelines and proactively proposing innovative, scalable solutions.
Ability to thrive in a cross-functional matrix, working seamlessly with bench biologists, automation engineers, and medicinal chemists.
Excellent ability to distill complex computational data and algorithmic concepts into clear, actionable insights for non-computational stakeholders.

Nice To Haves

High level of agility and comfort working in a fast-paced, newly formed team environment where processes are actively being built and refined.
Familiarity with Laboratory Information Management Systems (LIMS) and large-scale data management.
A demonstrated track record of implementing novel automation platforms and workflows that have significantly impacted drug discovery programs.
Familiarity with relevant disease areas (e.g., metabolic syndrome, autoimmunity, allergy, hematology) or biology themes (e.g., immunology, energy expenditure, platelet function).

Responsibilities

Mentor scientists and technicians and foster a collaborative and innovative team environment.
Collaborate with the department head to implement big data architectures that seamlessly capture, process, and QC data from scaled functional assays.
Analyze and interpret high-throughput screening campaigns.
Ensure the quality and reliability of screening data.
Build and execute computational workflows to analyze primary and secondary high-throughput screening (HTS) data, accelerating hit identification and the triage of peptide candidates.
Work with biology to adapt and scale of cell-based and biochemical assays for automated platforms, including target engagement assays.
Work closely other teams in Discovery to support their bioinformatic needs.
Apply predictive modeling, machine learning, and Large Language Models (LLMs) to extract meaningful insights from diverse biological data streams and automate complex data interpretations.
Leverage large-scale human multi-omics data (genomics, transcriptomics) and clinical datasets to identify, analyze, and prioritize novel therapeutic targets in immunology and metabolic diseases.