20 beste Stellen als phd engineering in berlin – aktuell auf Personalsuche

Data Scientist / Data Engineer
Nucs AI —Berlin
- Vollzeit
- Hybrides Arbeiten
- Doktorat
- Informatik
- Master
Direkt bewerben
Junior AI Engineer (w/m/d)
FLEX Capital Management GmbH —Berlin
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Direkt bewerben
Sr. Project Manager - Scientific RWE Projects (f/m/x)
D4L data4life gGmbH —Berlin
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Oliver Wyman - Data & Analytics Consulting - Intern (m/f/d) - Berlin
Oliver Wyman —Berlin
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Applied Scientist - LLM, Alexa Conversational Modelling Intelligence
Amazon Development Center Germany GmbH —Berlin
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Boston Consulting Group —Berlin
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Emerson —Berlin
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Delivery Manager (m/f/d)
MSA Safety —Berlin
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- Master
Machine Learning Engineer
Sensmore —Berlin
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Direkt bewerben
Senior Machine Learning Scientist / Data Engineer - Logistics Algorithms (all genders)
Zalando —Berlin
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Crystalization Expert (F/M/D)
Theion GmbH —Berlin
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Direkt bewerben
Snr Electrochemical Engineer
Ucaneo Biotech GmbH —Berlin
- Vollzeit
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Direkt bewerben
Acquisitions Editor Physical Sciences (f/m/d)
Koninklijke Brill B.V. —Berlin
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MSA, The Safety Company —Berlin
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Software Engineer
Moody's —Berlin
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Forward Deployed Geospatial Engineer - SAR Intelligence, Berlin
ICEYE —Berlin
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Senior Applied Scientist - Demand Forecast (all genders)
Zalando —Berlin
- Vollzeit
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Applied Scientist II, Amazon Robotics
Amazon Development Center Germany GmbH —Berlin
- Vollzeit
- Doktorat
- Informatik
- Master
4 Tage

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Data Scientist / Data Engineer

Nucs AI
Berlin

Direkt bewerben

Details zur Stelle

Vollzeit

Qualifikationen

Doktorat
Informatik
Master
Medizinische Bildverarbeitung
Graphdatenbanken

Vollständige Stellenbeschreibung

About Nucs AI

Nucs AI is revolutionizing cancer care through cutting-edge AI and medical imaging technology. Founded in 2024 by a multidisciplinary team of oncologists, AI researchers, and healthcare innovators, we’re tackling one of medicine’s most pressing challenges: the growing demand for accurate, timely cancer diagnostics in the face of rising scan volumes and limited radiologist capacity.

We sit at the intersection of diagnostics and treatment planning - building AI-powered tools at the convergence of medical imaging, radioligand therapy, and artificial intelligence. Starting with prostate cancer and expanding across oncology, we partner with world-leading medical institutions and pharmaceutical companies across the US, Europe, and Australia to bring precision oncology into everyday clinical practice.

Our mission is to enhance diagnostic precision and expand access to expert-level cancer care, improving patient outcomes worldwide. We’re venture-backed, early-stage, and building a team that blends deep clinical expertise with engineering intensity - moving with the rigor the medical field demands and the speed the problem deserves.

What you'll do

Build auditable data pipelines for large clinical, diagnostic, and medical imaging datasets in the cloud.
Own statistical analysis across clinical studies, diagnostic performance, model evaluation, and data quality.
Apply classical machine learning and deep learning methods to data analysis problems.
Automated ontology induction from medical documents using large language models.
Build dashboards and data observability tooling.
Maintain strong data lineage, provenance, traceability, and reproducibility across data workflows.
Produce analyses and supporting evidence that hold up in regulatory submissions and audits.

What we're looking for

A master's degree or PhD in computer science, data science, engineering, mathematics, statistics, physics, economics or a related discipline
3+ years of hands-on experience in data engineering or a closely related field, with demonstrated development of production-grade data solutions Proficiency in SQL and Python and software-development standards such as Git-based workflows, automated testing, code reviews and CI/CD
Comfort working with medical imaging formats including DICOM and NIfTI.
Practical experience with classical machine learning and explainable ML.
Working fluency with deep learning and modern LLM tooling.
Experience with cloud data infrastructure. We use GCP, but equivalent platforms are fine.
A strong working understanding of data lineage, provenance, traceability, and reproducibility.
Unusual attention to detail around data completeness, validity, consistency, and edge cases.
Flexibility at adapting to new technologies
Awareness of good software practices

Strongly preferred

Experience with medical imaging -clinical trials, pharmaceutical, healthcare or another regulated industry is an advantage
Experience with knowledge graphs / temporal knowledge graphs
Experience producing statistical analyses or technical evidence used in a regulatory submission.
Experience with model interpretability techniques such as SHAP.

Why Nucs AI

Mission with real impact – Your work directly improves how cancer patients are diagnosed and treated.
Ground-floor opportunity – Early-stage company, meaningful equity, and outsized influence on the direction we take.
World-class collaborators – Work alongside leading oncologists, nuclear medicine physicians, and AI researchers globally.
Massive market tailwinds – Radioligand therapy and AI-driven oncology are multi-billion dollar growth markets.
Autonomy and flexibility – Remote-first, flexible working. We hire great people and trust them to deliver.
Equity upside – Competitive equity package. We’re building something big and want you to share in it.

How to Apply

Submit your resume and a brief note on why this role and Nucs AI excite you.

Equal Opportunity

Nucs AI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all team members. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

Direkt bewerben

Erweiterte Suche

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Ich möchte aktuelle Job-E-Mails für Stellen als phd engineering in berlin erhalten

Weitere Job-Standorte erkunden

About Nucs AI

What you'll do

What we're looking for

Strongly preferred

Why Nucs AI

How to Apply

Equal Opportunity

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