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SCADA Commissioning Engineer
GE Grid Solutions, LLC
Remote, United States
…testing, and maintenance activities for Supervisory Control and Data Acquisition (SCADA), Substation Automation Systems (SAS), and Energy Management Systems (EMS). This role ensures safe…
Added 2 mins ago
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Software Engineer - Mobile Crowdsourcing Platform
Calder
Redwood City, CA
- $125,000 to $250,500 USD / year
- Design reliable data transfer pipelines that move large volumes of sensor, video, and media data from devices to phones to the cloud, with chunking, resumable uploads, retries,…
Added 2 mins ago
C
Senior Software Engineer - Platform
Calder
Redwood City, CA
- $179,000 to $250,500 USD / year
- Design and operate scalable GPU and CPU compute pipelines for 3D data processing workloads (SLAM, reconstruction, Gaussian Splatting training, dataset extraction)
Added 4 mins ago
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Staff Nuclear Engineer
Radiant Industries
El Segundo, CA
- $195,713 to $262,500 USD / year
…can be used for critical infrastructure like military bases, data centers, hospitals, and remote sites, as well as the commercial main street businesses that keep America running. Founded…
Added 5 mins ago
Guidance and Control Engineer II - TS/SCI
JPL/NASA
Pasadena, CA
…responsible for technology development, advanced concepts, design, development, delivery, integration and test, verification and validation, and operation of complex Mechanical, Thermal,…
Added 5 mins ago
AO
Enterprise Architect
Administrative Office of the Courts
Olympia, WA
- $9,478 to $12,437 USD / month
Ten (10) years of progressively responsible experience working in the development and design of complex information systems, IT Design, Enterprise strategies and service management, and use…
Added 6 mins ago
Senior Consultant, Data & Analytics
FTI Consulting Technology LLC
Los Angeles, CA · Washington, DC · Dallas, TX · NY · Boston, MA · Chicago, IL · San Francisco, CA
Design and build data pipelines, data models, and analytical workflows to ingest, integrate, transform, and validate large, complex datasets from disparate sources.
Added 8 mins ago
SB
Scientist, Product Transfer
Spear Bio
Remote, United States
- $95,000 USD / year
- · Lead NPI design transfer and complete all Product Development Process requirements.
Added 8 mins ago
Construction Project Manager
First Coast Security
Shreveport, LA
We are looking for a Construction Project Manager to run physical security scope on an active data center build for one of our largest enterprise clients. The site is a data center campus…
Added 8 mins ago
Construction Project Manager
First Coast Security
St. Louis, MO
We are looking for a Construction Project Manager to run physical security scope on an active data center build for one of our largest enterprise clients. The site is a data center campus…
Added 8 mins ago
Flavorist - Principal Scientist
PepsiCo
Valhalla, NY
Design experiments to test hypotheses, collect data and present results to reach business results.
Added 10 mins ago
VI
Industrial Engineer Intern
Viasat, Inc.
Duluth, GA
- $20.91 to $56.97 USD / hour
…Lean Practitioner as needed, you will identify inefficiencies, design data-driven solutions, and implement process improvements to drive operational excellence. You will work on optimizing…
Added 10 mins ago
VI
Industrial Engineer Intern
Viasat, Inc.
Tempe, AZ
- $20.91 to $56.97 USD / hour
…Lean Practitioner as needed, you will identify inefficiencies, design data-driven solutions, and implement process improvements to drive operational excellence. You will work on optimizing…
Added 11 mins ago
Senior Director, Immunology- AI Systems
Janssen Research & Development, LLC Legal Entity
Remote, United States
Provide technical leadership and informed challenges on AI solution design, data readiness, model suitability, validation, scalability, interoperability, and responsible use.
Added 12 mins ago
Infra Delivery Technician
Amazon Data Services, Inc.
Lancaster, TX
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all…
Added 17 mins ago
JD
Part-Time Student - Engineering Tech - Springfield, MO
John Deere
Springfield, MO
- $15 to $40 USD / hour
- Part-time
- Support implementation of new products and current products Continuous Improvement running design changes
Added 22 mins ago
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Data & Analytics Lead
GPAC
Los Angeles, CA
- $120,000 to $180,000 USD / year
Build the data foundation: Design and develop a data warehouse or lake integrating internal systems with external data sources, including partner APIs, vendor feeds, and performance data.
Added 23 mins ago
G
Supply Chain Development Engineer
GPAC
St Charles, MI
- $70,000 to $90,000 USD / year
Performance Optimization: Design and deploy actionable vendor improvement strategies targeting measurable gains in production lead times, piece-price reduction, and first-time quality.
Added 23 mins ago
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Supply Chain Development Engineer
GPAC
Chesaning, MI
- $70,000 to $90,000 USD / year
Performance Optimization: Design and deploy actionable vendor improvement strategies targeting measurable gains in production lead times, piece-price reduction, and first-time quality.
Added 23 mins ago
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Supply Chain Development Engineer
GPAC
Hemlock, MI
- $70,000 to $90,000 USD / year
Performance Optimization: Design and deploy actionable vendor improvement strategies targeting measurable gains in production lead times, piece-price reduction, and first-time quality.
Added 23 mins ago
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Supply Chain Development Engineer
GPAC
Clio, MI
- $70,000 to $90,000 USD / year
Performance Optimization: Design and deploy actionable vendor improvement strategies targeting measurable gains in production lead times, piece-price reduction, and first-time quality.
Added 23 mins ago
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Supply Chain Development Engineer
GPAC
Montrose, MI
- $70,000 to $90,000 USD / year
Performance Optimization: Design and deploy actionable vendor improvement strategies targeting measurable gains in production lead times, piece-price reduction, and first-time quality.
Added 24 mins ago
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Community Services Program Coordinator
City of Davis
Davis, CA
- $34.75 to $42.24 USD / hour
Added 27 mins ago
Minor League Assistant Pitching Coach
Philadelphia Phillies - Baseball Operations
Reading, PA
…on-field coaching skills with an ability to leverage technology, data, and collaboration to support player development across all levels of the…
Added 30 mins ago
Manufacturing & Quality Engineer (H-53 Heavy Lift Helicopter)
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Conduct quality research and data analysis to provide support in the establishment of M&QE requirements and management of M&QE efforts through all acquisition phases, including capacity…

Deliverome Bio

Founding Computational Scientist, Proteomics

Cambridge, MA, United States

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Job details

Posting language: English

Original job description

About the Deliverome Project Deliverome Bio is a nonprofit startup building a first-of-its-kind open atlas of surface protein abundance and internalization. We’re hiring a founding team to generate the data that could expand what targeted therapies can reach. The Role You will build and own the computational side of our proteomics platform: the pipelines, analysis, and data infrastructure that turn raw spectra from surface-enrichment experiments into quantitative measurements of the human surfaceome that we can compare across experiments and release publicly. This role is primarily scientist-facing. The people at the bench are who you serve first, and much of the work is building QC, reports, and result formats they can use directly without waiting on you. You will also contribute to our broader computational and data infrastructure, including how samples, metadata, and files are tracked, because the person who understands the data model should help decide how the data gets recorded in the first place. We have an Evosep LC and an Orbitrap Astral Zoom, and we plan to run them at high sample throughput across many cell types and conditions. The data volumes and reprocessing demands that come with that need to be planned for from the beginning rather than handled once we are behind. We are flexible on whether compute lives in the cloud, on local hardware, or both. What we care about is scale, reproducibility a year later, and being able to release everything we generate. We currently run Spectronaut and are open to changing or adding to it, and we would value your perspective on the tradeoffs between commercial and open-source stacks at this throughput. We also need someone who can diagnose the full workflow, not only the analysis. Surface proteomics can fail at labeling chemistry, enrichment specificity, digestion, chromatography, acquisition, search parameters, normalization, and statistics. We are looking for someone who can review a set of runs, say where the problem most likely sits, and propose the experiment that distinguishes between the remaining possibilities. That means knowing the wet lab well enough to push on experimental design while it is being decided, not after the samples are made. This is a rare opportunity to build a public data resource from the first sample onward. No standard exists for how surfaceome abundance and internalization data should be quantified, QC'd, and compared across cell types and labs, and you will have unusual latitude to set one. Everything you build, including pipelines, spectral libraries, QC metrics, benchmarks, and the atlas itself, will be openly released and used by drug developers and academic labs worldwide. Like all of our founding hires, you will have a direct line to the co-founders and a genuine say in how the platform is built. You will gain practical, shareable expertise across large-scale MS analysis, research data infrastructure, and open data release that flexibly advances your career in either industry or academia. What You Will Do Analysis infrastructure at scale

Build, containerize, and maintain pipelines for bottom-up LC-MS/MS analysis, DIA and DDA, that run reproducibly across hundreds to thousands of files
Own the stack decisions: search and quantification software, workflow orchestration, compute and storage architecture, and cost
Build the data model and provenance layer, covering sample and run metadata, parameter capture, versioned reprocessing, and the ability to answer which pipeline version produced a given number a year later
Make reprocessing routine, so that improved methods are applied across the full corpus and not only to new data

Quantification, statistics, and the atlas

Design the quantification strategy for comparability across cell types and experiments, including normalization, batch structure, missing value handling, and protein inference and rollup
Implement differential and ranking statistics with error control that holds up in review and in reuse by others
Move toward absolute or ratio-anchored abundance estimates where the biology calls for it, and be explicit about the assumptions behind any copies-per-cell number
Explore data completeness across cell and tissue types to understand where more data is needed, or when aspects of the atlas are sufficiently statistically empowered
Build the atlas as a versioned, queryable resource with annotation and topology integration, confidence tiers, and a clear separation between what we measured and what we inferred

Scientist-facing tools and research infrastructure

Build QC reports, run-level dashboards, and result formats that let bench scientists check and interrogate their own data
Partner with lab operations on the infrastructure upstream of analysis, including sample and cell line tracking, electronic records, metadata capture at the point of experiment, and file handoff conventions
Own storage, backup, and data lifecycle for large instrument datasets, including what stays available, what gets archived, and what gets deposited
Contribute to our general computational tooling as needs come up, and be someone colleagues can bring a data problem to

Integration and open science

Deposit raw and processed proteomics data to ProteomeXchange/PRIDE or MassIVE with metadata that makes reuse practical, and facilitate deposition of sequencing data to GEO and SRA
Co-author methods and resource papers, and release pipelines and analysis code publicly
As we scale and publish our data, integrate proteomic abundance with pooled screening readouts, transcriptomic references, and public surfaceome resources to produce interpretable target rankings and open data viewers
Reanalyze published surfaceome and cell-surface capture datasets to benchmark our own results and to build on work the field has already done

What We Are Looking For Required

PhD in computational biology, computer science, proteomics, or a related field, or equivalent depth built in industry
Deep hands-on experience analyzing large-scale bottom-up proteomics data, with fluency in at least one modern search and quantification stack (Spectronaut, DIA-NN, FragPipe/MSFragger, AlphaDIA, MaxQuant, Skyline). We run Spectronaut today, but experience matters more to us than the specific tool
Experience running analyses at scale, cloud or local, using containerized and orchestrated workflows (Nextflow, WDL, Snakemake, or similar)
Working command of quantitative proteomics statistics: normalization, batch effects, missing value structure in DIA versus DDA, protein inference, and FDR estimation
Proficiency in Python and version control with git/GitHub, including releasing tagged, reproducible pipelines

Highly valued

Experience with AWS (preferred) or equivalent, including object storage lifecycle management and batch or spot compute for large reprocessing jobs
Demonstrated ability to reason about the upstream experiment, including enrichment chemistry, sample preparation, LC, and instrument behavior, well enough to tell whether a failure is biological, chemical, or computational
Experience supporting bench scientists directly by building tools they can run themselves
Experience with electronic lab notebooks, LIMS, or sample tracking systems, and views on how to capture metadata in a busy lab
Building data resources that outside groups use: portals, APIs, versioned releases, FAIR metadata
Integration with orthogonal data types, including pooled screens, transcriptomics, membrane topology prediction, and existing surfaceome annotation sets
Experience with or interest in AI coding tools (Claude Code, Codex) as part of daily work

Who you are

You're a platform builder: you think about reproducibility, documentation, and what it takes for someone else to run your pipeline
You care about getting the measurement right, not just getting a number: you know what a given search setting, normalization choice, or FDR method assumes
You go upstream: when results look wrong you ask about the labeling reaction and the chromatography, not just the code
You build for the scientists around you, and would rather ship a tool a colleague can run than answer the same request every week
You know how to define the minimum viable analysis that answers this week's question while building toward a dataset that stays useful for a decade
You want your work to be adopted and reused by others, and your time to go towards problems that impact society
You thrive in a small, high-trust team where everyone's contributions are visible and decisions are made fast, and where accelerating science should never be perceived as stepping on toes

Level and Title We are hiring at the Scientist through Principal Scientist level depending on capability and experience, and we prefer candidates who have built a platform or data product in industry. What matters is depth in large-scale MS data analysis, the judgment to make an analysis reproducible and releasable, and enough experimental fluency to tell us what isn't working and why. What We Offer

Competitive salary benchmarked to industry rates
Full benefits including health, dental, and retirement
A founding team role: your decisions will shape the platform and the organization
Open science by design: your work will be published and used globally
Unprecedented collaboration with world-class advisors across proteomics, functional genomics, targeted delivery, and AI
A culture that values rigor, transparency, and speed, but doesn’t mistake busyness for productivity

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Skills

Workflow
Statistics
Research
Computer science
Snakemake
Estimating
Python
GitHub
AWS
Sample preparation
LIMS
Documentation
Data analysis

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