Postdoctoral Researcher in Tabular Foundation Models for Building and District Energy Systems — Empa
- Lieu
- Dübendorf
- Contrat
- full-time
- Publié
- il y a 10 jours
Vue d’ensemble du poste
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.
Exigences principales
- 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
Processus de candidature
- 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.
Contacts
- Applications sent via email or post will not be considered.
Détails supplémentaires
- 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
Notes et contenu original
- 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:
Questions sur cette offre
Quel salaire propose Empa pour ce poste ?
Empa indique CHF 73 500 - 111 500 bruts par an pour ce poste à Dübendorf. Il s'agit du salaire publié dans l'annonce d'origine (ou, si l'employeur ne précise pas de montant, d'une estimation réaliste pour le rôle et le secteur) — le calculateur de ce site le convertit en net réel une fois l'impôt frontalier et les cotisations sociales appliqués.
Est-ce un poste à temps plein, et quel type de contrat propose Empa ?
Cette offre est un poste en temps plein. Le type de contrat affiché ici provient directement de l'annonce originale de l'employeur ; confirmez toujours les horaires exacts, le préavis et la durée d'essai avec Empa pendant le processus de candidature, ces détails pouvant varier même au sein de la même catégorie de contrat.
Ai-je besoin d'un permis de frontalier pour un poste dans le canton de Zurich ?
Les résidents UE/AELE domiciliés dans la zone frontalière du pays voisin du canton de Zurich peuvent demander un permis G ; l'employeur suisse le dépose auprès de l'office cantonal des migrations après signature du contrat. Les règles de zone frontalière et les délais varient selon le pays voisin et le canton — confirmez les détails auprès de l'office des migrations du canton de Zurich ou avec les RH pendant la candidature.
Comment postuler à ce poste chez Empa ?
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