Category: Thèse

Deadline for PhD Application: noon 1 December, 2022

Hi all,
 
I am looking to recruit 2-3 PhD students to join the inaugural cohort of
doctoral students in the Computational Precision Health (CPH) program at UC
Berkeley and UCSF (See details and link for the application form below). If
you are a prospective PhD student interested in joining my lab, please
reach out to me via email and apply to CPH using the link below. I am
looking for students with backgrounds in Computer Science, Electrical
Engineering, Statistics, Biostatistics, Biomedical Informatics,
Computational Biology, and Bioengineering.
 
You can reach out to me directly if you have any questions:
amalaa@berkeley.edu.
 
 
Regards,
 
Ahmed Alaa
 
Assistant Professor at UC Berkeley and UCSF
 
——————————————————————————————————————————————————
Computational Precision Health (CPH) is an exploding field across both
academia and industry. This rapidly evolving field integrates the
tremendous advances in data science and data availability that have
occurred over the past decades with expertise in clinical medicine, public
health, and health care systems to enable a paradigm shift in the ways we
treat and prevent disease. Advances in data and analytics open the door to
faster deployment of more effective health interventions, but this
potential can only be achieved if the underlying computational and analytic
tools are conceived, tested, and validated for the health and health care
needs of diverse individuals and communities. The field of Computational
Precision Health aims to realize this potential.
A new PhD in Computational Precision Health will begin enrollment in fall
2023!
Applications are open September 15, 2022–January 6, 2023.
 
*Details on the application process:* https://cph1.wpengine.com/admissions/
<https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fcph1.wpengine.com%2Fadmissions%2F&data=05%7C01%7C%7C941fceba0b9446fc408b08da9c30cf00%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637994030687478009%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=wyuFhyKa994HzHZZy3kgvanOGwcS%2FKyEVPUZf3txuXo%3D&reserved=0>

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PhD in Statistics and Computer Science – a.y. 2023-2024
Call for applications for PhD student positions

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The Bocconi PhD School (Milan, Italy) provides 7 scholarships for the PhD
in Statistics and Computer Science, and a position with tuition waiver.

• Scholarship amount *
  20,000 euros per annum

Further funding may be available through teaching and research
assistantship.
Visit www.unibocconi.eu/admissionphd for detailed information.

** Applications are due by February 1, 2023 **

Within the PhD School at Bocconi University, the four-year PhD program in
Statistics and Computer Science is a high profile and rigorous doctoral
program that develops strong mathematical, statistical, computational and
programming backgrounds.

The curriculum is structured into two tracks: Statistics and Computer
Science. The first year includes courses that are compulsory for all
enrolled PhD students. The second-year features track-specific and elective
courses that provide students with a more specialized competence and focus
on topics that may be the object of the doctoral dissertation.

Dedicated mentorship is offered to students throughout their time at
Bocconi. Multidisciplinary interchange with other graduate programs in
Bocconi’s PhD School, as well as research experience abroad, are also
encouraged.

The Faculty includes internationally acknowledged top researchers in
Statistics, Computer Science, Machine Learning, Decision Theory and
Statistical Physics. The program also benefits from contributions of
authoritative visiting professors who deliver short monographic courses.

Highly qualified and motivated students with M.Sc. degrees in Statistics,
Mathematics, Computer Science, Economics, Physics, Engineering and related
areas, as well as other quantitatively-oriented fields, are encouraged to
apply for admission.

Applicants should hold, or be on their way to hold, a graduate degree or
equivalent.

For further information about the PhD program in Statistics and Computer
Science at Bocconi, visit www.unibocconi.eu/phdstatscompscience and feel
free to contact:
Antonio Lijoi (antonio.lijoi@unibocconi.it)
Angela Baldassarre, PhD administrative assistant
(angela.baldassarre@unibocconi.it)

I would appreciate it if you could circulate the below information to your networks. I am planning to recruit two new doctoral students (beginning in September 2023) and some positive number of new Master’s students (also beginning in September 2023). Also, there are multiple postdoctoral opportunities available at McGill and in Montreal (beginning in May 2023 or later). 
Those who are interested in a postdoctoral position should apply to the following postings: 
November 11 deadline: https://www.mathjobs.org/jobs?joblist-1067-20525
December 15 deadline: https://www.mathjobs.org/jobs/list/21313
Those who are interested in a doctoral position should apply here: 
January 15 deadline: https://www.mcgill.ca/gradapplicants/how-apply

In both cases, applicants should mention my name as a potential supervisor. 
Applicants who would like to work with me should be interested in probability and its interactions with other subjects (e.g. combinatorics, graph theory, PDEs), and should ideally have background in some of these areas. However, all applications will be carefully considered, including from those with non-traditional academic trajectories. 
Applicants can find out some things about my research interests on my website: http://problab.ca/louigi/. They are also welcome to contact me in advance of applying if they have questions. I especially welcome applications from members of groups who are traditionally underrepresented within mathematics. 
Sincerely,

Louigi (he/his).

Applications to the Gatsby Unit PhD programme close soon.

See www.ucl.ac.uk/gatsby/study-and-work/phd-programme

The Gatsby Unit is a leading research centre focused on theoretical
neuroscience and machine learning. We study (un)supervised and
reinforcement learning in brains and machines; inference, coding and neural
dynamics; Bayesian and kernel methods, and deep learning; with applications
to the analysis of perceptual processing and cognition, neural data, signal
and image processing, machine vision, network data and nonparametric
hypothesis testing. The unit provides a unique opportunity for a critical
mass of theoreticians to interact closely with one another, with the
Sainsbury Wellcome Centre for Neural Circuits and Behaviour (SWC), the
Centre for Computational Statistics and Machine Learning (CSML), other
research groups in related UCL departments, and the nearby Alan Turing and
Francis Crick Institutes.

Students complete a 4-year PhD in either machine learning or theoretical
neuroscience, with minor emphasis in the complementary field. Courses in
the first year provide a comprehensive introduction to both fields and
systems neuroscience. Students are encouraged to work and interact closely
with researchers at the SWC and/or CSML to take advantage of this uniquely
multidisciplinary research environment.

Applicants should have a strong analytical and quantitative background, a
keen interest in neuroscience, machine learning or both, and a relevant
first degree, for example in Mathematics, Statistics, Computer Science,
Engineering, Physics, Neuroscience or Cognitive Psychology.

Full funding is available regardless of nationality. The unit also welcomes
applicants who have secured or are seeking funding from other sources.
Applications should be submitted directly via our online portal.