Anders Andersson

Professor at KTH Royal Institute of Technology

KTH Royal Institute of Technology
Country flagSweden

Research Interests

Explore related searches

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

Positions (1)

Publisher
source

Josephine Sullivan

University Name
.

KTH Royal Institute of Technology

The Division of Robotics, Perception and Learning at KTH Royal Institute of Technology invites applications for a doctoral student position focused on image representations for class discovery. This WASP-funded project aims to advance generative approaches for out-of-distribution discovery and novel species identification, with a particular emphasis on fine-grained classification tasks such as plankton species identification. The research will integrate genomic measurements into the identification process, developing robust algorithms that are application area independent but with environmental and biological relevance. The successful candidate will join a collaborative environment involving Associate Professor Josephine Sullivan (RPL), Professor Anders Andersson (Environmental Genomics, SciLife Lab), and Bengt Karlson (SMHI). The PhD student will also be part of the WASP graduate school, benefiting from interdisciplinary expertise and scientific output, as highlighted in the article "The ocean's smallest creature is mapped." The project offers opportunities to contribute to cutting-edge research in computer vision, deep generative learning, and environmental genomics. Applicants must meet the eligibility requirements for postgraduate education as outlined by the Swedish Higher Education Ordinance. This includes holding a second cycle degree (such as a master's) or equivalent, or completing at least 240 higher education credits with 60 at the second-cycle level. Practical proficiency in deep learning programming libraries (TensorFlow, PyTorch, JAX) is mandatory, and experience with GPU-based experimentation and cluster computing (Docker, Slurm) is advantageous. English proficiency equivalent to English B/6 is required. Selection criteria include academic achievements, completed courses, demonstrated programming ability, and personal skills such as independence, collaboration, professionalism, and analytical thinking. Specialization in computer vision and/or machine learning is highly desirable. The position is full-time, temporary, and offers a monthly salary according to KTH's doctoral student salary agreement. Employment is for up to four years, with renewal options, and includes employee benefits and a supportive workplace. The doctoral student may perform limited additional tasks (up to 20%) related to training and administration. The position is based in Stockholm, Sweden, and may be subject to security clearance if classified as security-sensitive. To apply, candidates must submit a complete application through KTH's recruitment system, including certified copies of diplomas, grades, proof of language requirements, CV, and relevant publications or technical reports. Applications must be received by midnight CET on the closing date. For further information, contact Associate Professor Josephine Sullivan at [email protected]. KTH Royal Institute of Technology is a leading international technical university committed to education, research, and innovation for a sustainable society. The university values equality, diversity, and equal opportunities, offering a creative and dynamic environment for personal and professional growth.

5 months ago

Articles (13)

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Year:

2021

Year:

2020

Collaborators (20)

Andreia Miraldo

Head of Biodiversity

BaSS

PORTUGAL
View details

Karin Holmfeldt

Associate professor Professor

Linnéuniversitet

SWEDEN
View details

Agneta Andersson

Professor

Umeå Universitet Teknisk-Naturvetenskaplig Fakultet

SWEDEN
View details

Cecilie Svenningsen

Københavns Universitet

DENMARK
View details

Daniel Lundin

Assistant professor

Linnaeus University

SWEDEN
View details

Katherine D. McMahon

Professor

University of Wisconsin-Madison

UNITED STATES
View details

Meriel Jennifer Bittner

Københavns Universitet

DENMARK
View details

Domenico Simone

Istituto Zooprofilattico Sperimentale dell'Umbria e delle Marche

ITALY
View details

Francisco J. A. Nascimento

-

SWEDEN
View details

Erin Bertrand

Assistant Professor and Canada Research Chair

-

CANADA
View details

Ayco Tack

Stockholm University

SWEDEN
View details

Meike Anna Christine Latz

KTH Royal Institute of Technology

SWEDEN
View details

Piotr Łukasik

Assistant Professor

Jagiellonian University

POLAND
View details

Anders G. Finstad

Norwegian University of Science and Technology

NORWAY
View details

Anders Torstensson

Swedish Meteorological and Hydrological Institute

SWEDEN
View details

Monika Prus-Frankowska

Jagiellonian University

POLAND
View details

Sara Beier

Leibniz Institute for Baltic Sea Research

GERMANY
View details

Lasse Riemann

Professor

University of Copenhagen

DENMARK
View details

Sarahi L. Garcia

Assistant Professor

Stockholm University

SWEDEN
View details

Fredrik Ronquist

Professor

Swedish Museum of Natural History

SWEDEN
View details
ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.