Postdoctoral Research Fellow (AI / ML for Metabolic Modellingfor Biotechnology Chassis Optimisation (BII)

A postdoctoral research fellow position (junior postdoc /

senior postdoc) is available in the Breitling group in the

Bioinformatics Institute (BII), A

• STAR, Singapore in the area of

Artificial Intelligence (AI) and Machine Learning (ML) for

Metabolic modelling for biotechnology chassis

optimisation .

In the Breitling

group, we believe that computational approaches can make a real

difference for scientific progress in the life sciences. We are

committed to academic excellence and have created tools, such as

antiSMASH, ipaPy2, RankProd and Selenzyme, that are used by

thousands of researchers in academia and industry world-wide. We

value curiosity, creativity and innovation, and support the

intellectual growth and career development of our team members.

Alumni of the Breitling group have moved on to build their own

start-up companies and have joined the faculty of major

universities.

The successful candidate will be

part of an interdisciplinary team working on the development of

computational tools to support the Design-Build-Test-Learn cycle of

synthetic biology, in close collaboration with the team of

experimental scientists at A

Integrative Biosystems & Engineering Research Strategic

Research and Translational Thrust (SIBER

SRTT).

Job

Descriptions : Develop

and validate novel AI and ML models and methods for Metabolic

modelling for biotechnology chassis optimisation.

Apply these and other state-of-the-art computational

tools to inform, guide and support the work of experimental

biologists and biosystems engineers.

Work

closely with the other members of the computational synthetic

biology team in BII, as well as with the team of experimental

biologists at SIBER SRTT, to realise the shared mission of driving

synthetic biology advances towards industrial

implementation.

Present findings at seminars,

meetings and national / international conferences.

Write manuscripts for publication in high-impact

scientific journals.

Prepare high-quality

software for use by the wider community of researchers.

Apply proactively for individual research grants as part

of career development and contribute to the writing of larger grant

applications.

Build and maintain strong

relationships with the local and international research

network.

Requirements :

PhD in Computer Science, Bioinformatics, Computational

Biology, Biochemistry, Biotechnology, Chemical Engineering,

Microbiology or a related field.

Excellent

coding and software development skills, including proficiency in

Python and R programming.

Familiarity with

state-of-the-art computational tools, methodology and data formats

relevant for computational biology and bioengineering, with a

special focus on molecular biology and metabolic

engineering.

Passion for joining a growing and

dynamic group of researchers and a demonstrated ability to work

independently as well as collaboratively and efficiently in an

interdisciplinary team.

Desire to work closely

with experimental biologists to develop tools to drive the new

green revolution towards decarbonisation and sustainable chemical

production.

Track record of peer-reviewed

scientific publications in internationally recognised

journals.

Excellent communication skills both

written and spoken, especially for the preparation of scientific

manuscripts and reports.

A strong interest in

the translational and applied aspects of research, including

collaborations with industrial

partners.

Preferred

Skills : Whether you are an

experienced bioinformatician excited about the possibilities of

artificial intelligence, or a biology-curious machine learning

expert looking for new exciting applications across disciplines, we

want to hear from you. A strong willingness to learn and develop

new skills is highly preferred. We will be looking for candidates

with any of the following qualities :

Experience with the application of AI / ML tools for the

automated parameterisation of genome-scale metabolic models and the

generation of AI virtual cells.

Familiarity

with the tools and concepts of constraint-based metabolic

modelling, including resource-constrained models, metabolic network

reconstruction and metabolic flux analysis.

Deep understanding of the methodology, aims and concepts

of microbial strain engineering for biotechnology.

Strong background in AI / ML modelling, statistics, and

data analysis and visualization, preferably including practical

experience with deep learning frameworks (e.g., TensorFlow,

PyTorch).

Extensive domain knowledge in

(bio)chemistry, molecular biology, microbiology and the concepts of

synthetic biology / engineering biology.

Familiarity with the techniques of agentic

AI.

We

offer : A nurturing,

supportive and stimulating environment with close mentorship to

develop your scientific career and shape the future of synthetic

biology through innovative computational approaches.

An opportunity to work closely with an ambitious team of

experimental biologists at the forefront of advances in synthetic

biology.

Access to state-of-the-art

technologies, scientific resources, core facilities and

infrastructure housed within A

work.

Access to collaborations with industrial

partners to translate research findings to commercial applications

and societal impact.

We welcome applicants

from all

background.

The above

eligibility criteria are not exhaustive. A

additional selection criteria based on its prevailing recruitment

policies. These policies may be amended from time to time without

notice. We regret that only shortlisted candidates will be

notified.