Research Assistant
vor 2 Monaten
**Das Aufgabengebiet umfasst u. a.**:
Join the Cutting-Edge World of Deep Learning for Medical Image Analysis
This position offers the chance to work with real-world healthcare data to derive disease state labels using advanced data-driven methods. You'll tackle exciting challenges like self-supervised learning, leveraging category theory and symmetry-exploiting methods for noisy and incomplete labels, domain adaptation, and human-in-the-loop approaches. Your work will directly contribute to advancing medical diagnosis, treatment, and healthcare systems.
What We Offer
- A vibrant research environment within an internationally renowned lab.
- The opportunity to publish in leading venues and journals like MICCAI, CVPR, ECCV, IEEE TMI, ICLR, ICML, NeurIPS, Nature, and Medical Image Analysis.
- Collaboration with world-class partners at institutions like Stanford, MIT, Imperial College London, and NYU, with potential for extended research stays.
- A competitive salary aligned with TV-L regulations (~€55,000/year).
- Additional benefits including operational pension schemes, flexible working hours, remote work options, and excellent family-work compatibility.
Key Responsibilities
- Conduct world-class research, presenting and publishing results at top-tier conferences and journals.
- Active contribution to the lab’s research mission, including collaboration with clinical, industrial, and academic partners.
- Teaching responsibilities, including up to 5 SWS (semester weekly hours), depending on the position's co-funding.
- Support in supervising BSc, MSc, and PhD projects.
**Notwendige Qualifikation**:
Essential Qualifications
- A Master's or PhD in Computer Science, Mathematics, or a related field.
- Strong foundation in machine learning, computer vision, or medical image analysis.
- Proven programming skills in Python (plus tools like R, Unix shell scripting, etc.), demonstrated through past projects or public repositories.
- Excellent communication, English language skills, and a structured, independent work style.
**Wünschenswerte Qualifikation**:
Desirable Qualifications
- A strong publication track record for your career stage, including papers in MICCAI, CVPR, ECCV, or prestigious Q1 journals like IEEE TMI and Medical Image Analysis.
- Experience in teaching, research organization, or industrial collaboration.
- Familiarity with self-supervised learning, category theory, or human-in-the-loop systems is a bonus
Why FAU? FAU is a progressive, inclusive employer in a city with an excellent quality of life, short commutes, and a thriving academic and cultural community. Our lab has won international awards and prizes, and we pride ourselves on pushing boundaries in medical deep learning. You'll join a team that values curiosity, collaboration, and cutting-edge innovation.
**Bemerkungen**:
Interested? Please send:
- A cover letter outlining your motivation and fit for the role.
- A CV, including your publication list.
- A 2-page research statement describing your vision for future work.
- Copies of certificates and contact details for at least one reference.
**Stellenbeschreibung**:
- Beabsichtigte Eingruppierung je nach Qualifikation und persönlichen Voraussetzungen:
Entgelt-/Bes.Gr.**:TV-L E13 - 100%**:
- Zeitliche Befristung: 2-3 years Befristungsgrund: befr. Forschungsvorhaben.
- Es handelt sich um eine Vollzeitstelle.
- Sonstiges:
- Voraussichtlicher Einstellungstermin: 01.04.2025.
**Die Bewerbungsfrist endet zum: 28.2.2025.**:
**Für Auskünfte steht Ihnen zur Verfügung**:
Prof. Dr. Kainz, Bernhard
Department Artificial Intelligence in Biomedical Engineering (AIBE)
W3-Professur für Image Data Exploration and Analysis
**Die Bewerbungen sind zu richten an**:
Prof. Dr. Kainz, Bernhard
Department Artificial Intelligence in Biomedical Engineering (AIBE)
W3-Professur für Image Data Exploration and Analysis
Werner-von-Siemens Str. 61
91052 Erlangen
**Hinweise für Bewerber/-innen**
**Bitte fügen Sie der Bewerbung - auch dann, wenn Sie bereits an der Universität beschäftigt sind und sich für eine andere Stelle interessieren - bei**:
- **Ihren Lebenslauf**
- ** Sämtliche Schulabschluß-, Ausbildungs
- und Arbeitszeugnisse**
Für alle Stellenausschreibungen gilt: Die Friedrich-Alexander-Universität fördert die berufliche Gleichstellung der Frauen. Frauen werden deshalb ausdrücklich aufgefordert, sich zu bewerben.
Schwerbehinderte im Sinne des Schwerbehindertengesetzes werden bei gleicher fachlicher Qualifikation und persönlicher Eignung bevorzugt berücksichtigt, wenn die ausgeschriebene Stelle sich für Schwerbehinderte eignet. Details dazu finden Sie in der jeweiligen Ausschreibung unter dem Punkt "Bemerkungen".
Bei Wunsch der Bewerberin, des Bewerbers, kann die Gleichstellungsbeauftragte zum Bewerbungsgespräch hinzugezogen werden, ohne dass der Bewerberin, dem Bewerber dadurch Nachteile entstehen.
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