Postdoctoral Researcher in Tabular Foundation Models for Building and District Energy Systems — Empa
- Località
- Dübendorf
- Contratto
- full-time
- Pubblicato
- 10 giorni fa
Panoramica
Materials science and technology are our passion.
With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living.
Empa is a research institution of the ETH Domain.
- Materials science and technology are our passion.
- With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living.
- We seek a highly motivated and dedicated researcher with a PhD in mathematics, electrical or mechanical engineering, computer science or a related field, and a strong methodological background in machine learning.
- The ideal candidate has demonstrated research experience with foundation models , including the evaluation and adaptation of pre-trained models, fine-tuning strategies, and the development of new model architectures or learning approaches.
Requisiti principali
- We seek a highly motivated and dedicated researcher with a PhD in mathematics, electrical or mechanical engineering, computer science or a related field, and a strong methodological background in machine learning.
- The ideal candidate has demonstrated research experience with foundation models , including the evaluation and adaptation of pre-trained models, fine-tuning strategies, and the development of new model architectures or learning approaches.
- Experience with tabular foundation models or foundation models for structured data is particularly relevant to this position. Key qualifications include:
- Strong research experience in deep learning and foundation models, including experience with pre-trained models, fine-tuning, transfer learning, or self-supervised learning.
- Experience with tabular foundation models or foundation models for structured data is particularly relevant.
- A strong understanding of modern deep-learning architectures and training strategies, and experience designing and rigorously evaluating new machine-learning methods.
- Excellent Python programming skills and strong hands-on experience implementing, training, and evaluating deep-learning models and research codebases. A strong track record in machine learning or closely related fields Excellent written and spoken English Ideally, the candidate also:
- Has experience in energy system modeling and optimization
- Has experience with tabular or heterogeneous data, particularly across multiple da-tasets, domains, or tasks
- Is familiar with mathematical optimization methods, such as mixed-integer linear programming
- Has experience with uncertainty quantification, surrogate modelling or physics-informed machine learning
- Has an understanding of the technical challenges associated with the energy transition Our offer
Processo di candidatura
- Evaluate and benchmark existing pre-trained tabular foundation models for building- and district-scale energy applications, assessing their transferability and generalization across systems, operating conditions, and downstream tasks.
- Adapt and fine-tune existing foundation models for energy-system applications, investigating efficient adaptation strategies and the use of domain-specific data and knowledge.
- Develop new tabular foundation-model approaches where existing pre-trained models are insufficient, with a particular focus on transferability across heterogeneous energy systems and datasets.
- Validate and benchmark the developed models using building measurements , physics-based simulations and energy-system optimization models.
- Investigate how tabular foundation models can support energy-system modelling and optimization , including applications such as prediction, surrogate modelling, uncertainty quantification, and decision support.
- Coordinate the joint research activities between UESL and IMOS.
- Publish and present research perspectives and results.
- Contribute to research proposals and the acquisition of competitive funding.
Contatti
- Applications sent via email or post will not be considered.
Dettagli ulteriori
- The position combines Empa UESL’s expertise in developing and accessing energy system models with the methodological expertise of the IMOS Laboratory in machine learning and foundation models.
- Experience with tabular foundation models or foundation models for structured data is particularly relevant to this position. Key qualifications include:
- Excellent Python programming skills and strong hands-on experience implementing, training, and evaluating deep-learning models and research codebases. A strong track record in machine learning or closely related fields Excellent written and spoken English Ideally, the candidate also:
- Has an understanding of the technical challenges associated with the energy transition
Note e contenuto originale
- Your tasks
- Your profile
- Experience with tabular foundation models or foundation models for structured data is particularly relevant to this position.
- Key qualifications include:
- Excellent Python programming skills and strong hands-on experience implementing, training, and evaluating deep-learning models and research codebases.
- A strong track record in machine learning or closely related fields
- Excellent written and spoken English
- Ideally, the candidate also:
Domande frequenti su questo annuncio
Che stipendio offre Empa per questa posizione?
Empa indica CHF 73'500 - 111'500 lordi annui per questo ruolo a Dübendorf. Questo è lo stipendio pubblicato nell'annuncio originale (o, quando il datore non specifica una cifra, una stima realistica per ruolo e settore) — il calcolatore di questo sito lo converte nel netto reale una volta applicate imposta da frontaliere e contributi sociali.
È un ruolo a tempo pieno, e che tipo di contratto offre Empa?
Questo annuncio è una posizione a tempo pieno. Il tipo di contratto mostrato qui arriva direttamente dall'annuncio originale del datore di lavoro; conferma sempre orario esatto, preavviso e durata del periodo di prova con Empa durante il colloquio, perché questi dettagli possono variare anche all'interno della stessa categoria contrattuale.
Serve un permesso da frontaliere per un ruolo nel canton Zurigo?
I residenti UE/AELS nella zona di frontiera del paese confinante con il canton Zurigo possono richiedere il Permesso G; il datore di lavoro svizzero lo presenta all'ufficio della migrazione di quel canton dopo la firma del contratto. Regole sulla zona di frontiera e tempi di lavorazione variano per paese confinante e canton — verifica i dettagli con l'ufficio della migrazione del canton Zurigo o con HR durante il colloquio.
Come mi candido a questa posizione presso Empa?
Usa il pulsante "Candidati ora" in questa pagina — rimanda direttamente all'annuncio originale di Empa su apply.refline.ch, quindi la tua candidatura arriva direttamente nel sistema di gestione candidature del datore di lavoro. Frontaliere Ticino non raccoglie né inoltra candidature in proprio.
