Postdoc in Machine Learning for Computational Biology

School of Electrical Engineering and Computer Science at KTH

Job description

We are looking for a Machine Learning Specialist with an emphasis in Computational Biology. In this role, you will be part of an interdisciplinary team studying human development and disease processes through understanding different cell types and their functions. The successful candidate will work in the Lagergren group, CST KTH, on the development of Variational Auto-Encoders (VAEs) to effectively construct lineage trees in collaboration with the Frisén group, KI, which will use the innovative LUSTRE technique to generate data. You will be performing tasks such as:

(1) Develop, optimize, and apply machine learning methodologies to decipher complex biological data derived from techniques like LUSTRE and Smart-seq3. (2) Collaborate with the team to develop and fine-tune Variational Auto-Encoders (VAEs). (3) Assist in developing distance-based and Bayesian methods for lineage tree reconstruction based on VAE computed distances or latent variables. (4) Analyze datasets from human blood and brain cells and cancer.

What we offer

• You will be working in a group with great experience and international contacts
• You will be physically located at Scilifelab, an international well-known hub for biomedical research
• A position at a leading technical university that generates knowledge and skills for a sustainable future.
• Engaged and ambitious colleagues along with a creative, international and dynamic working environment
• Help to relocate and be settled in Sweden and at KTH

Read more about what it is like to work at KTH

Qualifications

Requirements

• A doctoral degree or an equivalent foreign degree. This eligibility requirement must be met no later than the time the employment decision is made.
• PhD degree in Computer Science, Computational Biology, Bioinformatics, or a related field. This eligibility requirement must be met no later than the time the employment decision is made.
• Strong expertise in Machine Learning, specifically deep learning methodologies such as Variational Auto-Encoders (VAEs).
• Solid background in computational biology and genomics, including knowledge of cell lineage, spatial transcriptomics, and gene expression measurement techniques.
• Proficiency in Python and other programming languages common in machine learning and bioinformatics such as R.
• Research expertise
• Teaching abilities
• Awareness of diversity and equal opportunity issues, with specific focus on gender equality
• Collaborative abilities
• Independence

Preferred qualifications

• A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline
• Familiarity with machine learning libraries and tools (TensorFlow, PyTorch, Keras, scikit-learn, etc.).
• Experience with phylogenetic methodologies, Bayesian methods, and distance-based lineage tree reconstruction is a strong plus.
• Demonstrable ability to work with large biological datasets.
• Strong communication skills to collaborate effectively in a highly interdisciplinary team.
• Demonstrable track record of scientific publications in computational biology and machine learning is a plus.
• Ability to think creatively and apply innovative approaches to solve complex biological questions.

Great emphasis will be placed on personal skills.

Trade union representatives

You will find contact information to trade union representatives at KTH’s webbpage.

To apply for the position

Log into KTH’s recruitment system in order to apply for this position. You are the main responsible to ensure that your application is complete according to the ad. 

The application must include:

• CV including relevant professional experience and knowledge.
• Copy of diplomas and grades from your previous university studies. Translations into English or Swedish if the original documents have not been issued in any of these languages.
• Briefly explain why you want to conduct research, your academic interests and how they relate to your previous studies and future goals. Max two pages long.
• At least two references

Your complete application must be received at KTH no later than the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time).

About the employment

The position offered is for, at the most, two years.

A position as a postdoctoral fellow is a time-limited qualified appointment focusing mainly on research, intended as a first career step after a dissertation

Others

Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values.

For information about processing of personal data in the recruitment process please read here.

We firmly decline all contact with staffing and recruitment agencies and job ad salespersons.

Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.